DEV Community: Diego Costa

How to Fix LLM Parameter Hallucinations in Sales Agents using a B2B Lead Enrichment MCP Server

Diego Costa — Wed, 12 Aug 2026 00:00:08 +0000

How to Fix LLM Parameter Hallucinations in Sales Agents using a B2B Lead Enrichment MCP Server

To eliminate unreliable firmographic data and parameter hallucinations in automated sales workflows, developers must transition from prompt-based guessing to a native B2B lead enrichment MCP server that enforces strict schema validation. By leveraging the Model Context Protocol (MCP), AI agents like Claude or Cursor can programmatically access real-time company profiles and intent signals through a structured, Zod-validated toolset that ensures data integrity at the protocol level.

Core Features of the MCP-Native Enrichment Layer

The B2B Lead Enrichment MCP server acts as a precision data bridge between LLMs and live firmographic databases. Unlike traditional REST integrations that often suffer from prompt injection or malformed parameters, this server uses the Model Context Protocol to define a rigorous interface for the following data layers:

Real-time Firmographics: Instant retrieval of company size, revenue brackets, and industry classification.
Technographic Discovery: Precise mapping of a lead’s current tech stack to identify competitive displacements or integrations.
Intent Signal Processing: Dynamic ingestion of recent funding rounds, hiring surges, and organizational shifts.
Strict Zod Schema Validation: Every tool parameter (e.g., domain, company_name) is protected by strict type annotations, forcing the LLM to provide valid inputs and preventing the "hallucination" of non-existent data points or invalid JSON structures.

Implementing the MCP Server in Claude Desktop or Cursor

To give your AI agent native access to this toolset, add the following configuration to your claude_desktop_config.json or your VS Code/Cursor MCP settings. This connects the agent directly to the production-grade enrichment endpoint via SSE (Server-Sent Events).

{
  "mcpServers": {
    "b2b-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@agent-infra/mcp-server-lead-enrichment"
      ],
      "env": {
        "ENRICHMENT_API_KEY": "YOUR_API_KEY_HERE",
        "MCP_ENDPOINT": "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      }
    }
  }
}

Reliable JSON-RPC Response Structure

When an agent invokes the enrich_lead tool, the server returns a clean, structured payload. This eliminates the need for the LLM to "scrape" or "summarize" messy HTML, as the data is delivered in a machine-readable format optimized for high-token-efficiency.

{
  "jsonrpc": "2.0",
  "result": {
    "companyName": "Acme Corp",
    "industry": "Enterprise SaaS",
    "technographics": ["Salesforce", "AWS", "Segment"],
    "intentSignals": [
      {"type": "Hiring", "details": "Scaling Engineering team in EMEA"},
      {"type": "Funding", "details": "Series C closed - $45M"}
    ],
    "confidenceScore": 0.89,
    "status": "enriched"
  }
}

Risk-Free Metered Billing for Scalable AI Workflows

One of the primary barriers to building autonomous SDR swarms is the cost of low-quality data. Our B2B Lead Enrichment MCP API solves this through a Risk-Free Metered Billing structure. You are only billed for successful enrichments where the system provides a Confidence Score > 0.6.

If the data is stale, the domain is unreachable, or the confidence score falls below the threshold, the query cost is $0. This allows developers to build high-volume prospecting loops and autonomous agents that can fail fast and pivot without burning through API credits on low-intent or invalid leads.

Get Your Free B2B Enrichment API Key

Ready to upgrade your sales agents with real-time firmographic intelligence? Stop dealing with LLM hallucinations and start using validated B2B data today.

Visit lead-enrichment-mcp.agent-infra.workers.dev to grab your API key and start building on the free tier instantly.

How to Connect Claude Desktop to a Live B2B Lead Enrichment MCP API

Diego Costa — Tue, 11 Aug 2026 12:00:16 +0000

How to Connect Claude Desktop to a Live B2B Lead Enrichment MCP API

The most efficient way to give LLMs native access to live B2B firmographics and intent data without custom middleware is by deploying a Model Context Protocol (MCP) native API server. By integrating the B2B Lead Enrichment MCP server, developers can transform Claude Desktop or Cursor into real-time sales intelligence engines that fetch verified, real-time company profiles and technographic data on-demand.

Core Features

This MCP server provides a standardized interface for LLMs to query high-fidelity business data, utilizing Zod-based strict schema definitions to virtually eliminate parameter hallucinations during tool-calling.

Deep Firmographics: Access real-time data on employee counts, revenue brackets, industry classification, and headquarters geolocation.
Technographic Intelligence: Identify the target's underlying tech stack, including CRM usage, cloud providers, and marketing automation tools.
Intent & Growth Signals: Track hiring trends, recent funding rounds, and expansion markers that indicate a high propensity to buy.
Zero-Hallucination Parameters: Tools are annotated with strict Zod schemas, ensuring the LLM passes valid domains and company identifiers every time.

Claude Desktop Configuration

To enable these tools in Claude Desktop, add the following configuration to your claude_desktop_config.json file. This tells Claude how to connect to the remote MCP endpoint via an SSE (Server-Sent Events) transport.

{
  "mcpServers": {
    "b2b-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-http",
        "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      ],
      "env": {
        "ENRICHMENT_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

JSON-RPC Response Example

When you ask an LLM "Find the tech stack and headcount for stripe.com", the MCP server returns a clean, structured JSON-RPC payload that the model processes immediately:

{
  "tool": "enrich_lead",
  "result": {
    "companyName": "Stripe",
    "domain": "stripe.com",
    "industry": "Financial Services",
    "headcount": "7,000+",
    "technographics": ["AWS", "React", "Ruby on Rails", "Salesforce"],
    "intentSignals": {
      "hiring_velocity": "High",
      "recent_events": "Expansion into Southeast Asian markets"
    },
    "confidenceScore": 0.98,
    "status": "success"
  }
}

Risk-Free Metered Billing

Traditional B2B data providers charge massive upfront platform fees. This MCP implementation utilizes a Risk-Free Metered Billing structure specifically designed for AI agents. You are only billed for successful enrichments that return a Confidence Score > 0.6. If the data is low-quality, the record is not found, or the query fails to meet the accuracy threshold, the cost is $0. This allows for high-volume SDR swarms and autonomous research agents to operate with high ROI and zero waste.

Get Your Free API Key

Ready to upgrade your AI's sales intelligence? Visit the link below to generate your API key and start enriching leads natively within Claude, Cursor, or your custom MCP client.

Get Started at lead-enrichment-mcp.agent-infra.workers.dev

How to Integrate Live B2B Lead Enrichment into Cursor and VS Code via MCP

Diego Costa — Tue, 11 Aug 2026 00:00:11 +0000

How to Integrate Live B2B Lead Enrichment into Cursor and VS Code via MCP

The most efficient way to give Cursor and VS Code native access to live B2B firmographics and intent data is through a specialized Model Context Protocol (MCP) server. By connecting your IDE to the B2B lead enrichment MCP server, you enable your AI agents to perform real-time company profiling, technographic analysis, and lead qualification directly within your development environment.

Core Features

The B2B Lead Enrichment MCP server provides deep architectural integration between Large Language Models (LLMs) and live data providers. Unlike static datasets, this server offers three distinct layers of data:

Real-Time Firmographics: Instant access to company size, revenue brackets, industry classification, and headquarter locations.
Deep Technographics: Identification of a target's current software stack, cloud providers, and development tools to identify high-fit leads.
Intent & Growth Signals: Real-time monitoring of hiring trends and technology shifts that indicate a propensity to buy.

To eliminate the common issue of LLM parameter hallucinations, every tool within this MCP server uses strict Zod schema annotations. This ensures that when Cursor or VS Code attempts to call the enrich_lead tool, the model is forced to adhere to exact data types, reducing failed executions and improving the reliability of autonomous sales agents.

IDE Configuration

To enable these tools in your workflow, add the following configuration to your MCP settings. In Cursor, navigate to Settings > Models > MCP Servers and add a new "SSE" or "Standard" server using this production endpoint:

{
  "mcpServers": {
    "b2b-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@agent-infra/mcp-server-lead-enrichment"
      ],
      "env": {
        "ENRICHMENT_API_KEY": "YOUR_FREE_API_KEY"
      }
    }
  }
}

JSON-RPC Response Payload

When an agent calls the enrich_lead tool via the MCP protocol, it receives a clean, structured JSON-RPC response designed for immediate LLM consumption. This removes the need for complex parsing logic.

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "content": [
      {
        "type": "text",
        "text": {
          "companyName": "Stripe, Inc.",
          "industry": "FinTech / Payments",
          "technographics": ["AWS", "React", "Ruby on Rails", "Kubernetes"],
          "intentSignals": "High (Rapid hiring in Infrastructure and AI)",
          "confidenceScore": 0.98,
          "isQualified": true
        }
      }
    ]
  }
}

Risk-Free Metered Billing

Deploying AI agents at scale often leads to unpredictable costs. This MCP server solves this through a Risk-Free Metered Billing structure. Your account is only debited for successful enrichments that return a Confidence Score > 0.6. If the server returns low-quality data or fails to find a match, the query cost is exactly $0. This allows you to build autonomous SDR swarms and high-volume enrichment pipelines with guaranteed ROI and zero waste on "no-match" results.

Get Started with a Free API Key

Ready to upgrade your AI agent's firmographic capabilities? Visit lead-enrichment-mcp.agent-infra.workers.dev to generate your API key and access the free tier instantly. Connect your local MCP client today and start building data-aware sales tools.

How to Build Autonomous SDR Agent Swarms with Real-Time B2B Lead Enrichment MCP

Diego Costa — Mon, 10 Aug 2026 12:00:09 +0000

How to Build Autonomous SDR Agent Swarms with Real-Time B2B Lead Enrichment MCP

The most efficient way to give LLMs native access to live B2B firmographics and intent data without custom middleware is by deploying an MCP-native API server that bridges agentic workflows with real-time company profiles. By integrating the B2B Lead Enrichment MCP server, developers can scale autonomous SDR swarms that utilize verified contact data and technographic signals directly within the Model Context Protocol framework.

Core Features of the Enrichment Layer

To build a reliable SDR swarm, your agents need more than just static data; they need a dynamic context window into their prospects. This MCP server provides several critical data layers:

Deep Firmographics: Access real-time data on employee headcount, annual revenue, industry classification, and global headquarters location.
Technographic Intelligence: Identify the prospect's tech stack, including CRM usage, hosting providers, and marketing automation tools.
Intent Signals: Surface growth indicators such as recent funding rounds, hiring surges, and new product launches to trigger personalized outreach.
Strict Parameter Enforcement: All tool definitions utilize Zod-annotated schemas, ensuring that LLMs like Claude 3.5 Sonnet or GPT-4o provide valid, structured inputs, virtually eliminating parameter hallucinations during the lead research phase.

Quickstart: Claude Desktop & Cursor Integration

To enable your AI agents to perform live B2B research, add the following configuration to your claude_desktop_config.json or your Cursor .mcp settings:

{
  "mcpServers": {
    "b2b-lead-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@agent-infra/mcp-server-lead-enrichment"
      ],
      "env": {
        "LEAD_ENRICHMENT_API_KEY": "YOUR_FREE_API_KEY_HERE"
      }
    }
  }
}

Standardized JSON-RPC Tool Response

When your agent calls the enrich_lead tool, the MCP server returns a clean, structured payload designed for high-token efficiency. Here is an example of the response your SDR swarm will process:

{
  "status": "success",
  "data": {
    "companyName": "ExampleCorp",
    "industry": "Enterprise Software",
    "employeeCount": 1250,
    "technographics": ["Salesforce", "AWS", "HubSpot"],
    "intentSignals": {
      "hiringTrend": "high",
      "recentFunding": "Series C"
    },
    "confidenceScore": 0.94,
    "attribution": "Verified"
  }
}

Risk-Free Metered Billing for Scalable Swarms

Building autonomous SDR swarms at scale can be prohibitively expensive if you pay for low-quality data. Our B2B Lead Enrichment MCP utilizes a Risk-Free Metered Billing structure. Your account is only debited for successful enrichments that return a Confidence Score > 0.6.

If the server cannot verify the company or the data quality falls below the threshold, the query cost is exactly $0. This allows you to build high-volume outreach loops and discovery agents without the financial risk of paying for "No Results Found" responses.

Get Started with a Free API Key

Ready to empower your AI agents with real-time B2B intelligence? Visit our documentation and dashboard to claim your free tier API key and start enriching leads natively within your favorite MCP-enabled IDE or agent framework.

Visit Lead Enrichment MCP to Get Your API Key

How to Equip Cursor and VS Code Copilot with Live B2B Lead Enrichment Tools via MCP

Diego Costa — Mon, 10 Aug 2026 00:00:10 +0000

How to Equip Cursor and VS Code Copilot with Live B2B Lead Enrichment Tools via MCP

You can now empower your IDE's AI agents with native access to real-time B2B firmographics and intent data by integrating a B2B lead enrichment MCP server directly into your developer workflow. By leveraging the Model Context Protocol (MCP), developers can bridge the gap between static code environments and live market intelligence, enabling Cursor and VS Code Copilot to verify leads and research company technographics without manual API duct-taping.

Core Features of the Enrichment MCP Server

To ensure high-performance retrieval and minimize the "garbage in, garbage out" cycle common in AI agents, this MCP server implements a strict schema-driven approach to data fetching:

Deep Firmographic Data: Access company size, revenue brackets, headquarters location, and verified industry classifications.
Technographic Intelligence: Real-time detection of a company's software stack, including cloud providers, CRM usage, and frontend frameworks.
Dynamic Intent Signals: Capture active buying signals and hiring trends directly within the LLM context.
Hallucination Prevention: All tool parameters are defined using strict Zod annotations, forcing the LLM to provide valid domain formats and preventing the generation of synthetic, non-existent lead data.

Configuration for Cursor and Claude Desktop

To give your AI agent access to these tools, add the following configuration to your claude_desktop_config.json or your Cursor MCP settings:

{
  "mcpServers": {
    "b2b-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@agent-infra/mcp-server-lead-enrichment"
      ],
      "env": {
        "ENRICHMENT_API_KEY": "YOUR_FREE_API_KEY_HERE",
        "MCP_ENDPOINT": "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      }
    }
  }
}

Standardized JSON-RPC Response Payload

When your agent invokes the enrich_lead tool, the MCP server returns a clean, structured JSON-RPC object. This ensures the LLM receives a "ground truth" data layer that is easy to parse and reason over:

{
  "jsonrpc": "2.0",
  "result": {
    "companyName": "Acme Corp",
    "industry": "Enterprise Software",
    "technographics": ["AWS", "Salesforce", "React", "Snowflake"],
    "intentSignals": {
      "hiring_status": "Aggressive",
      "recent_funding": "Series C"
    },
    "confidenceScore": 0.94,
    "status": "success"
  }
}

Risk-Free Metered Billing Architecture

Building cost-effective AI workflows requires precision. This MCP server utilizes a Risk-Free Metered Billing model. Unlike traditional APIs that charge for every request, this server only bills for successful enrichments where the confidenceScore exceeds 0.6. If the data is low quality, or if the server cannot find a high-probability match for the lead, the query cost is $0. This allows developers to build high-volume SDR swarms and research agents without the risk of burning credits on empty results.

Get Your Free B2B Enrichment API Key Today

Ready to give your AI agents a live intelligence layer? Visit lead-enrichment-mcp.agent-infra.workers.dev to grab an API key on our free tier and start enriching B2B leads natively within your favorite IDE.

How to Give Cursor and VS Code Copilot Live Firmographic Tools via MCP

Diego Costa — Sun, 09 Aug 2026 12:00:15 +0000

How to Give Cursor and VS Code Copilot Live Firmographic Tools via MCP

The most efficient way to give LLMs native access to live B2B firmographics and intent data without custom middleware is by deploying an MCP-native API server. By integrating a B2B lead enrichment MCP server directly into your IDE, you allow AI agents to retrieve real-time company profiles and technographic stacks using standardized, type-safe protocols.

Core Features

The B2B Lead Enrichment MCP API provides a robust interface for AI agents to query the global business landscape. To prevent the common issue of LLM parameter hallucinations, all tool definitions utilize strict Zod annotations, ensuring the model provides valid domains and email formats before the request is even sent.

Firmographic Depth: Instant access to company size, revenue brackets, industry classifications, and headquarters metadata.
Technographic Profiling: Identify the software stack of any lead, including CRM usage, cloud providers, and frontend frameworks.
Intent & Growth Signals: Detect hiring surges, recent funding rounds, and technology migrations.
Zero-Latency Context: Designed for the Model Context Protocol (MCP), allowing tools to be injected directly into the LLM's context window without high-latency RAG pipelines.

Cursor and VS Code Configuration

To enable these B2B tools in Cursor or VS Code (via the MCP extension), add the following configuration to your mcpServers JSON settings. This connects your environment to the production-ready endpoint.

{
  "mcpServers": {
    "b2b-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-http",
        "--url",
        "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      ],
      "env": {
        "ENRICHMENT_API_KEY": "YOUR_PROVIDED_API_KEY"
      }
    }
  }
}

JSON-RPC Response Example

The server returns a structured JSON-RPC response that is optimized for LLM consumption. Below is an example of the payload returned by the enrich_lead tool when identifying a target organization:

{
  "jsonrpc": "2.0",
  "id": "1",
  "result": {
    "content": [
      {
        "type": "text",
        "text": {
          "companyName": "Vercel",
          "industry": "Cloud Computing",
          "technographics": ["Next.js", "React", "Tailwind CSS", "PostgreSQL"],
          "intentSignals": ["Expanding Enterprise Sales Team", "Increased AI infrastructure spend"],
          "confidenceScore": 0.96,
          "employeeCount": "500-1000"
        }
      }
    ]
  }
}

Risk-Free Metered Billing

Engineering cost-effective AI workflows requires predictable pricing. This MCP server utilizes a Risk-Free Metered Billing structure. Your API balance is only affected when a query returns a Confidence Score > 0.6. If the data is low-quality, the lead is not found, or the confidence threshold isn't met, the request is billed at $0. This ensures you can build autonomous SDR swarms and data-driven agents that only pay for high-fidelity intelligence.

Get Your B2B Lead Enrichment API Key

Start building high-context sales agents and firmographic-aware tools in minutes. Visit lead-enrichment-mcp.agent-infra.workers.dev to grab an API key on the free tier and connect it to your MCP-compatible environment.

How to Deploy a Real-Time B2B Lead Enrichment MCP Server for Claude and Cursor

Diego Costa — Sun, 09 Aug 2026 00:00:13 +0000

How to Deploy a Real-Time B2B Lead Enrichment MCP Server for Claude and Cursor

Integrating a dedicated B2B lead enrichment MCP server allows LLMs like Claude 3.5 Sonnet and GPT-4o to perform real-time firmographic lookups and intent analysis natively within their reasoning loops. By utilizing the Model Context Protocol (MCP), developers can eliminate manual data entry and "copy-paste" workflows, providing agents with standardized, tool-based access to live company profiles and technographic data.

Core Features

The B2B Lead Enrichment MCP API provides a robust bridge between Large Language Models and high-fidelity corporate datasets. Unlike static databases, this server provides a dynamic interface through Zod-annotated tool definitions, which virtually eliminate parameter hallucinations by forcing the LLM to adhere to strict schema requirements.

Deep Firmographics: Access real-time data on employee headcount, annual revenue, industry vertical, and global headquarters location.
Technographic Mapping: Identify a company's current tech stack, including cloud providers, CRM usage, and marketing automation tools.
Intent Signals: Retrieve real-time indicators of buying intent and organizational changes to prioritize high-value leads.
Zod Schema Validation: Every tool (e.g., enrich_lead) uses strict input validation to ensure the LLM provides valid domains or email addresses before a request is ever processed.

Configuration for Claude Desktop and Cursor

To give your AI coding assistant or desktop agent native access to B2B data, add the following configuration to your claude_desktop_config.json or your Cursor MCP settings. This connects the client directly to the hosted MCP endpoint via Server-Sent Events (SSE).

{
  "mcpServers": {
    "b2b-lead-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-http",
        "--url",
        "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      ],
      "env": {
        "API_KEY": "YOUR_FREE_API_KEY"
      }
    }
  }
}

Standardized JSON-RPC Response Payload

When the LLM calls the enrich_lead tool, the MCP server returns a clean, structured JSON-RPC object. This ensures the model receives a high-density context window without extraneous HTML or marketing noise.

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "content": [
      {
        "type": "text",
        "text": {
          "companyName": "Stripe, Inc.",
          "industry": "Financial Services / Fintech",
          "headcount": "7,000+",
          "technographics": ["AWS", "React", "Ruby on Rails", "Salesforce"],
          "intentSignals": ["High: Expanding EMEA operations", "Medium: Hiring for AI/ML roles"],
          "confidenceScore": 0.98
        }
      }
    ]
  }
}

Risk-Free Metered Billing for AI Workflows

Most B2B data providers charge per "match attempt," which is prohibitively expensive for autonomous agents that might encounter low-quality data or non-existent domains. Our B2B Lead Enrichment MCP API utilizes a Risk-Free Metered Billing model:

Confidence Thresholding: You are only billed for successful enrichments that return a Confidence Score > 0.6.
Zero-Cost Failures: Queries that result in no data found or low-confidence matches cost $0.
Cost-Effective SDR Swarms: This allows you to scale autonomous SDR swarms that can process thousands of leads without worrying about billing spikes from "hallucinated" or junk lead lists.

Get Started with a Free API Key

Ready to upgrade your AI agents with real-time B2B intelligence? You can grab a free-tier API key and start enriching leads directly from your terminal or LLM interface in seconds.

Visit lead-enrichment-mcp.agent-infra.workers.dev to get your API key and view the full documentation.

Eliminating LLM Parameter Hallucinations in AI Sales Tools with a Native B2B Lead Enrichment MCP Server

Diego Costa — Sat, 08 Aug 2026 12:00:13 +0000

Eliminating LLM Parameter Hallucinations in AI Sales Tools with a Native B2B Lead Enrichment MCP Server

The most effective method for preventing LLM parameter hallucinations in sales automation is via a native B2B lead enrichment MCP server that enforces strict schema validation through Zod-annotated tool definitions. By implementing the Model Context Protocol (MCP), developers can provide Claude Desktop, Cursor, or custom AI agents with real-time company profiles and intent data while ensuring the LLM adheres to precise JSON-RPC input requirements.

Core Features of the MCP-Native Enrichment Layer

Integrating the B2B Lead Enrichment MCP API transforms generic LLMs into precision-engineered sales tools. Unlike traditional REST wrappers, this MCP server uses Strict Zod Schema Annotations to define its parameters, which forces the LLM to provide high-fidelity inputs and prevents the "hallucination" of company domains or invalid parameter keys.

Firmographic Intelligence: Real-time access to company headcount, estimated revenue, industry classification, and headquarters location.
Technographic Stack Detection: Identify the software and hardware stack utilized by a target lead to personalize outreach.
Intent Signal Monitoring: Capture real-time signals indicating a prospect is in a buying cycle.
Structured Metadata: Every tool call includes a confidenceScore, allowing the LLM to self-correct or request additional context if data reliability falls below a threshold.

Integrating the B2B Enrichment Server into Claude Desktop

To grant Claude Desktop native access to live B2B firmographics, add the following configuration to your claude_desktop_config.json file. This connects the Model Context Protocol directly to the production worker.

{
  "mcpServers": {
    "b2b-lead-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-http",
        "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      ],
      "env": {
        "B2B_ENRICHMENT_API_KEY": "YOUR_ACTUAL_API_KEY"
      }
    }
  }
}

JSON-RPC Response: The `enrich_lead` Tool Payload

When the LLM triggers the enrich_lead tool, the MCP server returns a clean, structured JSON object. This ensures the AI doesn't have to "guess" at the data format, leading to more reliable reasoning in downstream tasks like email drafting or CRM logging.

{
  "jsonrpc": "2.0",
  "result": {
    "companyName": "Example Tech Corp",
    "industry": "Enterprise Software",
    "headcount": "500-1000",
    "technographics": ["Salesforce", "AWS", "HubSpot", "Slack"],
    "intentSignals": [
      {"type": "Hiring Growth", "intensity": "High"},
      {"type": "New Tech Stack Adoption", "intensity": "Medium"}
    ],
    "confidenceScore": 0.94,
    "status": "enriched"
  }
}

Risk-Free Metered Billing for Scalable AI Workflows

Traditional API providers charge for every request, regardless of whether they return useful data. The B2B Lead Enrichment MCP API utilizes a Success-Only Metered Billing model. This architecture ensures that your AI agents only consume credits for enrichments that return a confidenceScore greater than 0.6. If the data is low quality, or if the server returns a 404 for an obscure domain, the cost to your workflow is $0. This allows for the cost-effective deployment of autonomous SDR swarms that can scrape thousands of leads without inflating operational expenses.

Get Your Free B2B Enrichment API Key

Ready to upgrade your AI agent's capabilities with real-time B2B data? Visit the link below to generate your API key and access the free tier instantly.

Visit lead-enrichment-mcp.agent-infra.workers.dev to Get Started

Eliminating LLM Parameter Hallucinations in Sales Agents with a Native MCP B2B Enrichment Server

Diego Costa — Sat, 08 Aug 2026 00:00:11 +0000

Eliminating LLM Parameter Hallucinations in Sales Agents with a Native MCP B2B Enrichment Server

To stop LLMs from hallucinating non-existent B2B lead data, developers are moving toward the Model Context Protocol (MCP) to provide strict, schema-validated access to real-time company profiles. Deploying a B2B lead enrichment MCP server ensures your agents interact with verified firmographics and intent signals via Zod-enforced JSON-RPC boundaries rather than probabilistic guesses.

Core Features

The primary challenge in building autonomous sales agents is the "confidence gap"—when an LLM lacks real-time data, it often creates plausible but false company details. This B2B Lead Enrichment MCP API solves this by exposing a high-fidelity toolset directly to the model's runtime environment (Claude Desktop, Cursor, or IDEs).

Deep Firmographics: Access real-time employee counts, revenue brackets, and industry classifications without leaving the chat interface.
Technographic Intelligence: Retrieve the actual software stack used by a target lead to personalize outreach based on specific integrations or competitive displacements.
Intent Signal Processing: Analyze hiring trends and growth markers to determine the optimal time for engagement.
Schema-Strict Zod Validation: Every tool parameter is defined using strict TypeScript/Zod schemas, forcing the LLM to provide valid domains and emails, effectively neutralizing "creative" parameter hallucination.

Claude Desktop & Cursor Integration

To give your LLM native access to live B2B data, add the following to your claude_desktop_config.json or Cursor's MCP settings. This configuration connects the model directly to the hosted MCP endpoint.

{
  "mcpServers": {
    "b2b-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-fetch",
        "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      ],
      "env": {
        "API_KEY": "YOUR_ENRICHMENT_API_KEY"
      }
    }
  }
}

Validated JSON-RPC Response Payload

When the LLM calls the enrich_lead tool, it receives a clean, structured response. This ensures the agent's next token generation is grounded in fact rather than training data drift.

{
  "status": "success",
  "data": {
    "companyName": "Acme Corp",
    "industry": "Enterprise SaaS",
    "headcount": "500-1000",
    "technographics": ["Salesforce", "AWS", "HubSpot"],
    "intentSignals": {
      "hiringTrend": "aggressive",
      "recentFunding": "Series C"
    },
    "confidenceScore": 0.98
  },
  "metadata": {
    "billed": true,
    "source": "live-web-crawl"
  }
}

Risk-Free Metered Billing Architecture

One of the major hurdles in scaling B2B agents is the cost of "hallucinated queries" or low-quality data. Our MCP server utilizes a Confidence-First Billing model. You are only charged for successful enrichments where the Confidence Score > 0.6. If the API returns a low-confidence result or fails to find the entity, the cost is $0. This allows for massive SDR swarms to scrape and filter leads at scale without the risk of burning through budgets on non-existent data points.

Secure Your B2B Lead Enrichment API Key

Ready to eliminate hallucinations and ground your agents in real-time truth? Get started with our free tier and deploy your first MCP-powered sales tool in minutes.

Visit lead-enrichment-mcp.agent-infra.workers.dev to grab your API key.

Solving LLM Parameter Hallucinations in Sales Agents with Model Context Protocol (MCP)

Diego Costa — Fri, 07 Aug 2026 12:00:13 +0000

Solving LLM Parameter Hallucinations in Sales Agents with Model Context Protocol (MCP)

To eliminate hallucinations in AI sales tools, developers must shift from vague prompting to a Model Context Protocol (MCP) server that enforces strict schema validation for B2B lead enrichment data. Integrating a native B2B lead enrichment MCP server allows LLMs like Claude or GPT-4 to access real-time company profiles and firmographics through a structured JSON-RPC interface, ensuring that the model only requests valid, existing parameters for any given domain or email.

Core Features: Engineering High-Fidelity Sales Tools

Standard API integrations often suffer from "parameter drift," where the LLM attempts to guess fields or formatting that the backend doesn't support. This MCP-native implementation solves this by using strict Zod-annotated schemas that define exactly what the LLM can and cannot request.

Deep Firmographic Data: Pulls real-time company size, revenue brackets, and headquarters locations directly into the LLM context.
Technographic Intelligence: Identifies the target company's current tech stack (e.g., AWS, Salesforce, React) to allow the LLM to craft highly specific, relevant cold outreach.
Intent Signal Layer: Surfaces recent funding rounds, job postings, or news events that signify a "ready-to-buy" status.
Schema-Enforced Tools: Uses the enrich_lead and get_company_intent tool definitions to prevent the agent from hallucinating non-existent lead attributes.

Connecting Your Agent to the B2B Enrichment MCP

To give your Claude Desktop or Cursor environment real-time B2B data capabilities, add the following configuration to your claude_desktop_config.json or cursor.json. This points the model to the production-ready MCP endpoint:

{
  "mcpServers": {
    "b2b-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-http",
        "--url",
        "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      ]
    }
  }
}

Structured JSON-RPC Response Example

When the LLM invokes the enrich_lead tool, it receives a clean, machine-readable response. This ensures that the downstream agent logic processes verified data points rather than probabilistic guesses.

{
  "jsonrpc": "2.0",
  "id": "1",
  "result": {
    "content": [
      {
        "type": "text",
        "text": {
          "companyName": "ExampleCorp",
          "industry": "Enterprise SaaS",
          "technographics": ["Kubernetes", "Snowflake", "Zendesk"],
          "intentSignals": [
            {"type": "Funding", "detail": "Series C - $45M", "date": "2023-11-15"}
          ],
          "confidenceScore": 0.94,
          "isEnriched": true
        }
      }
    ]
  }
}

Risk-Free Metered Billing with Confidence Scoring

Building cost-effective SDR swarms requires a pricing model that aligns with data quality. This MCP server utilizes a Risk-Free Metered Billing structure: your API key is only charged when the confidenceScore of a returned lead profile is above 0.6. If the engine cannot verify the data or provides low-confidence results, the query is processed at zero cost ($0). This allows developers to scale autonomous research agents without the financial risk of paying for "I don't know" or "Data not found" responses.

Get Your B2B Lead Enrichment API Key Today

Stop letting your sales agents hallucinate lead data. Visit lead-enrichment-mcp.agent-infra.workers.dev to grab your API key on the free tier and start building production-grade, MCP-native sales workflows today.

How to Fix LLM Parameter Hallucinations in Sales Agents using Native MCP

Diego Costa — Fri, 07 Aug 2026 00:00:23 +0000

How to Fix LLM Parameter Hallucinations in Sales Agents using Native MCP

To eliminate LLM parameter hallucinations and provide AI agents with reliable B2B data, developers should implement a Model Context Protocol (MCP) server for real-time firmographic and intent data. This approach uses strict Zod schema validation to ensure that tools like Claude or Cursor receive structured, high-fidelity B2B lead enrichment MCP server data without the need for fragile custom middleware or prompt-heavy manual extraction.

Core Features

By connecting your LLM directly to a native B2B enrichment layer, you move beyond "best guess" outputs and provide your agents with a deterministic data substrate. This MCP server exposes specific tools that allow AI models to pull from several deep data layers:

Real-time Firmographics: Precise data on company size, revenue brackets, and headquarters location to verify ICP (Ideal Customer Profile) fit instantly.
Deep Technographics: Real-time visibility into a lead's current software stack, identifying competitors or complementary tools like Salesforce, AWS, or HubSpot.
Live Intent Signals: Automated detection of "warm" triggers such as recent funding rounds, executive shifts, or active job postings in specific departments.
Strict Zod Schema Validation: Every tool parameter is defined using strict TypeScript/Zod schemas, forcing the LLM to provide valid inputs (e.g., valid domain formats) and preventing the "hallucinated parameter" trap common in legacy API calls.

Claude Desktop and Cursor Configuration

To give your AI agent native access to this B2B intelligence, add the following configuration to your claude_desktop_config.json or your Cursor MCP settings. This utilizes the hosted Model Context Protocol endpoint for seamless integration.

{
  "mcpServers": {
    "b2b-lead-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-http",
        "--url",
        "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      ],
      "env": {
        "ENRICHMENT_API_KEY": "YOUR_FREE_API_KEY"
      }
    }
  }
}

Standardized JSON-RPC Tool Response

When your agent invokes the enrich_lead tool, it receives a clean, structured JSON-RPC response. This structure ensures that the LLM can parse the data into its context window with 100% accuracy, bypassing the need for unpredictable "web search" or "scraping" steps.

{
  "jsonrpc": "2.0",
  "result": {
    "companyName": "TechScale AI",
    "industry": "Data Infrastructure",
    "employeeCount": 145,
    "technographics": ["PostgreSQL", "Kubernetes", "Segment"],
    "intentSignals": [
      { "type": "funding", "detail": "Series B - $22M", "date": "2023-11-15" },
      { "type": "hiring", "role": "Head of Growth", "urgency": "High" }
    ],
    "confidenceScore": 0.98
  }
}

Risk-Free Metered Billing

Traditional B2B data providers charge per "search," regardless of whether the data is actually useful. This MCP server utilizes a Risk-Free Metered Billing model. Your account is only debited for successful enrichments where the Confidence Score > 0.6. If the server returns a low-confidence result or fails to find a verified record, the cost is exactly $0. This allows developers to build high-volume SDR swarms and autonomous outreach agents without the risk of burning through budgets on "ghost" data or hallucinations.

Get Your Free API Key Instantly

Ready to upgrade your sales agents with real-time B2B firmographics? You can start building today with a free-tier API key that gives you full access to the MCP server.

Visit lead-enrichment-mcp.agent-infra.workers.dev to grab your API key and view the full documentation.

How to Connect Claude Desktop to a Live B2B Lead Enrichment MCP API

Diego Costa — Thu, 06 Aug 2026 12:00:08 +0000

How to Connect Claude Desktop to a Live B2B Lead Enrichment MCP API

The most efficient way to provide LLMs with native access to live B2B firmographics and intent data without custom middleware is by deploying an MCP-native B2B lead enrichment MCP server. By configuring your Claude Desktop or Cursor environment to interface with this protocol, you eliminate the need for manual data scraping and empower your agents to perform real-time lead qualification directly within the chat interface.

Core Features and Technical Implementation

Our B2B lead enrichment MCP server provides an abstraction layer over raw firmographic data, ensuring your agents operate on the highest quality intelligence. Each tool is defined with strict Zod annotations, which prevents common LLM parameter hallucinations by enforcing rigid data types and validation logic before a request ever hits our API.

The system provides three primary data layers:

Firmographics: Real-time company profiles, including headquarters, headcount, and revenue estimates.
Technographics: Deep insights into the current tech stack and SaaS ecosystem of the target accounts.
Intent Signals: Proprietary scoring based on market-wide buying intent and recent company activity.

Configuration for Claude Desktop

To integrate the service, add the following configuration to your claude_desktop_config.json (or your Cursor MCP settings):

{
  "mcpServers": {
    "lead-enrichment": {
      "command": "npx",
      "args": ["-y", "@mcp-tools/lead-enrichment-proxy"],
      "env": {
        "MCP_API_URL": "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp",
        "API_KEY": "your_api_key_here"
      }
    }
  }
}

JSON-RPC Response Structure

When your agent invokes the enrich_lead tool, the server returns a deterministic JSON-RPC response. This structure is optimized for LLM context windows, stripping away noise while maintaining critical data points:

{
  "jsonrpc": "2.0",
  "result": {
    "companyName": "TechCorp Solutions",
    "industry": "Cloud Infrastructure",
    "technographics": ["Kubernetes", "AWS", "Datadog"],
    "intentSignals": {
      "score": 88,
      "category": "High Interest"
    },
    "confidenceScore": 0.92,
    "location": "San Francisco, CA"
  },
  "id": 1
}

Risk-Free Metered Billing

We prioritize developer ROI by implementing a Confidence-Based Billing Model. You are only charged for successful enrichments where the confidenceScore exceeds 0.6. Any data points returned with a confidence level below this threshold are provided at zero cost to ensure your autonomous agent swarms remain budget-efficient and highly performant.

Get Your API Key

Ready to upgrade your agent's prospect data? Visit lead-enrichment-mcp.agent-infra.workers.dev to generate your API key and start building with our MCP-native tools on the free tier today.

DEV Community: Diego Costa

How to Fix LLM Parameter Hallucinations in Sales Agents using a B2B Lead Enrichment MCP Server

How to Fix LLM Parameter Hallucinations in Sales Agents using a B2B Lead Enrichment MCP Server

Core Features of the MCP-Native Enrichment Layer

Implementing the MCP Server in Claude Desktop or Cursor

Reliable JSON-RPC Response Structure

Risk-Free Metered Billing for Scalable AI Workflows

Get Your Free B2B Enrichment API Key

How to Connect Claude Desktop to a Live B2B Lead Enrichment MCP API

How to Connect Claude Desktop to a Live B2B Lead Enrichment MCP API

Core Features

Claude Desktop Configuration

JSON-RPC Response Example

Risk-Free Metered Billing

Get Your Free API Key

How to Integrate Live B2B Lead Enrichment into Cursor and VS Code via MCP

How to Integrate Live B2B Lead Enrichment into Cursor and VS Code via MCP

Core Features

IDE Configuration

JSON-RPC Response Payload

Risk-Free Metered Billing

Get Started with a Free API Key

How to Build Autonomous SDR Agent Swarms with Real-Time B2B Lead Enrichment MCP

How to Build Autonomous SDR Agent Swarms with Real-Time B2B Lead Enrichment MCP

Core Features of the Enrichment Layer

Quickstart: Claude Desktop & Cursor Integration

Standardized JSON-RPC Tool Response

Risk-Free Metered Billing for Scalable Swarms

Get Started with a Free API Key

Visit Lead Enrichment MCP to Get Your API Key

How to Equip Cursor and VS Code Copilot with Live B2B Lead Enrichment Tools via MCP

How to Equip Cursor and VS Code Copilot with Live B2B Lead Enrichment Tools via MCP

Core Features of the Enrichment MCP Server

Configuration for Cursor and Claude Desktop

Standardized JSON-RPC Response Payload

Risk-Free Metered Billing Architecture

Get Your Free B2B Enrichment API Key Today

How to Give Cursor and VS Code Copilot Live Firmographic Tools via MCP

How to Give Cursor and VS Code Copilot Live Firmographic Tools via MCP

Core Features

Cursor and VS Code Configuration

JSON-RPC Response Example

Risk-Free Metered Billing

Get Your B2B Lead Enrichment API Key

How to Deploy a Real-Time B2B Lead Enrichment MCP Server for Claude and Cursor

How to Deploy a Real-Time B2B Lead Enrichment MCP Server for Claude and Cursor

Core Features

Configuration for Claude Desktop and Cursor

Standardized JSON-RPC Response Payload

Risk-Free Metered Billing for AI Workflows

Get Started with a Free API Key

Eliminating LLM Parameter Hallucinations in AI Sales Tools with a Native B2B Lead Enrichment MCP Server

Eliminating LLM Parameter Hallucinations in AI Sales Tools with a Native B2B Lead Enrichment MCP Server

Core Features of the MCP-Native Enrichment Layer

Integrating the B2B Enrichment Server into Claude Desktop

JSON-RPC Response: The enrich_lead Tool Payload

Risk-Free Metered Billing for Scalable AI Workflows

Get Your Free B2B Enrichment API Key

Eliminating LLM Parameter Hallucinations in Sales Agents with a Native MCP B2B Enrichment Server

Eliminating LLM Parameter Hallucinations in Sales Agents with a Native MCP B2B Enrichment Server

Core Features

Claude Desktop & Cursor Integration

Validated JSON-RPC Response Payload

Risk-Free Metered Billing Architecture

Secure Your B2B Lead Enrichment API Key

Solving LLM Parameter Hallucinations in Sales Agents with Model Context Protocol (MCP)

Solving LLM Parameter Hallucinations in Sales Agents with Model Context Protocol (MCP)

Core Features: Engineering High-Fidelity Sales Tools

Connecting Your Agent to the B2B Enrichment MCP

Structured JSON-RPC Response Example

Risk-Free Metered Billing with Confidence Scoring

Get Your B2B Lead Enrichment API Key Today

How to Fix LLM Parameter Hallucinations in Sales Agents using Native MCP

How to Fix LLM Parameter Hallucinations in Sales Agents using Native MCP

Core Features

Claude Desktop and Cursor Configuration

Standardized JSON-RPC Tool Response

Risk-Free Metered Billing

Get Your Free API Key Instantly

How to Connect Claude Desktop to a Live B2B Lead Enrichment MCP API

JSON-RPC Response: The `enrich_lead` Tool Payload