DEV Community: Diego Costa

How to Give Cursor and VS Code Copilot Live B2B Firmographic Tools via MCP

Diego Costa — Tue, 22 Sep 2026 12:00:13 +0000

How to Give Cursor and VS Code Copilot Live B2B Firmographic Tools via MCP

The most efficient way to provide LLMs with native access to live B2B firmographics and intent data without custom middleware is by deploying a B2B lead enrichment MCP server. By integrating this Model Context Protocol interface directly into your IDE, you enable Cursor and VS Code to resolve real-time company profiles and technographics as verified tool calls rather than relying on stale, hallucinated training data.

Core Features and Data Integrity

This MCP server exposes a standardized set of tool definitions that allow LLMs to query high-fidelity business intelligence endpoints. To eliminate the risk of LLM parameter hallucinations, all tools utilize strict Zod-based input validation, ensuring that queries for domain or companyName are structured correctly before the request ever hits the origin.

The data layers include:

Firmographic Data: Headcount, revenue range, and verified office locations.
Technographic Stack: In-depth detection of software procurement and infrastructure.
Intent Signals: Real-time triggers based on recent funding, job postings, and market activity.
Confidence Scoring: Every output includes a confidenceScore parameter, ensuring the agent only acts on data points exceeding a 0.6 threshold.

Configuration for Cursor and VS Code

To connect your IDE to the production endpoint, update your mcp.json configuration file located in your MCP settings directory. This enables the agent to natively invoke the enrich_lead function during your coding or research sessions.

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

Example JSON-RPC Response Payload

When the LLM calls enrich_lead, the API returns a structured object designed for immediate tokenization and reasoning:

{
  "jsonrpc": "2.0",
  "result": {
    "companyName": "Acme Corp",
    "industry": "SaaS / Fintech",
    "technographics": ["AWS", "Salesforce", "Segment"],
    "intentSignals": "Series C funding, high hiring velocity in engineering",
    "confidenceScore": 0.94,
    "status": "success"
  },
  "id": "req-12345"
}

Cost-Effective, Risk-Free Metered Billing

We understand that autonomous agents can be chatty. To protect your budget, this API utilizes a Risk-Free Metered Billing structure. You are only charged for successful enrichments where the returned confidenceScore is > 0.6. Queries that return low-quality data or fail to retrieve a company profile cost exactly $0, allowing you to scale your AI-driven SDR workflows without unpredictable infrastructure costs.

Get Your API Key

Ready to supercharge your development workflow with live B2B intelligence? Visit lead-enrichment-mcp.agent-infra.workers.dev to generate your API key and start utilizing enterprise-grade firmographic data within your IDE today.

How to Fix LLM Parameter Hallucinations in Sales Agents Using a Native MCP Server

Diego Costa — Tue, 22 Sep 2026 00:01:05 +0000

How to Fix LLM Parameter Hallucinations in Sales Agents Using a Native MCP Server

The most effective way to eliminate LLM parameter hallucinations in sales automation is by deploying a native Model Context Protocol (MCP) server that enforces strict Zod-validated schemas for real-time B2B lead enrichment. By integrating this specialized B2B lead enrichment MCP server, developers can provide LLMs with direct, structured access to live company profiles and intent signals, bypassing the reliability issues of traditional tool-calling methods.

Core Features of the B2B Enrichment MCP

Standard AI agents often struggle with "hallucinated parameters"—inventing company details or misformatting API requests. Our MCP-native architecture solves this by leveraging the Model Context Protocol, which establishes a rigid contract between the LLM and the data source.

Strict Schema Enforcement: Every tool in the server, such as enrich_lead and get_company_intent, is defined with strict Zod annotations. This ensures the LLM provides valid domains and identifiers, drastically reducing 400-level errors in automated workflows.
Multi-Layered Data Intelligence: Access three distinct data layers in a single call: Firmographics (revenue, headcount, industry), Technographics (current software stack), and Real-Time Intent Signals (recent funding, hiring surges, or technology shifts).
Native LLM Integration: Designed specifically for the next generation of AI IDEs and assistants, this server allows Claude Desktop, Cursor, and VS Code Copilot to "see" your B2B data tools as native capabilities.

Technical Configuration: Claude Desktop & Cursor

To give your local agent live B2B intelligence, add the following configuration to your claude_desktop_config.json or Cursor settings. This points the LLM to the production-grade MCP endpoint.

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

Structured JSON-RPC Response Example

When your agent calls the enrich_lead tool, it receives a clean, deterministic JSON response. This structure allows the LLM to reason over the data without guessing, making it perfect for autonomous SDR swarms.

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "companyName": "Stripe, Inc.",
    "industry": "FinTech / Payments",
    "technographics": ["React", "AWS", "Ruby on Rails", "Salesforce"],
    "intentSignals": [
      { "type": "Expansion", "description": "Increasing headcount in EMEA", "weight": 0.85 }
    ],
    "confidenceScore": 0.98,
    "status": "success"
  }
}

Risk-Free Metered Billing for AI Workflows

One of the biggest hurdles in building autonomous sales agents is the cost of "bad data." This MCP server implements a Risk-Free Metered Billing model. Instead of paying for every API hit, you are only billed for successful enrichments that return a Confidence Score > 0.6.

If the LLM triggers a query for a non-existent company, or if the data retrieved is low-confidence, the cost is exactly $0. This allows developers to scale agentic loops without the fear of burning through budgets on failed lookups or LLM loops.

Get Your Free API Key Instantly

Ready to upgrade your AI agents with real-time B2B intelligence and zero hallucinations? You can start building today on our free tier.

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

How to Give Cursor and Claude Desktop Live B2B Firmographic Tools via MCP

Diego Costa — Mon, 21 Sep 2026 12:00:14 +0000

How to Give Cursor and Claude Desktop Live B2B 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 a Model Context Protocol (MCP) native API server. By integrating the B2B Lead Enrichment MCP server, developers can transform Cursor, VS Code, or Claude Desktop into powerful sales intelligence tools that pull real-time company profiles directly into the AI’s active reasoning context.

Core Features

The B2B Lead Enrichment MCP API provides a standardized interface for LLMs to query deep organizational data. By leveraging Model Context Protocol, the server exposes tools that allow agents to browse:

Comprehensive Firmographics: Real-time industry classification, headcount growth, and revenue estimates.
Technographic Layers: Detection of active software stacks (SaaS, Cloud providers, CRM usage).
High-Intensity Intent Signals: Tracking organizational shifts that indicate a propensity to purchase.
Hallucination Prevention: Every tool parameter is defined using strict Zod annotations, ensuring the LLM passes correctly formatted domain names and filters, eliminating the common "parameter hallucination" found in traditional REST-to-Agent bridges.

Configuration for Cursor and Claude Desktop

To enable these tools, add the following configuration to your claude_desktop_config.json or your Cursor "External MCP" 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"
      ]
    }
  }
}

JSON-RPC Enrichment Response Example

When you ask an AI agent to "Enrich the company stripe.com," the MCP server executes the enrich_lead tool and returns a structured JSON-RPC response. This clean data allows the LLM to provide factual insights rather than guessing:

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "companyName": "Stripe, Inc.",
    "industry": "FinTech / Payments",
    "employeeCount": 8000,
    "technographics": ["AWS", "React", "Ruby on Rails", "Salesforce"],
    "intentSignals": ["Global expansion in APAC", "New regulatory compliance hiring"],
    "confidenceScore": 0.98
  }
}

Risk-Free Metered Billing

Traditional B2B data APIs charge per request, regardless of whether the data is found or accurate. This MCP server utilizes a Risk-Free Metered Billing structure specifically designed for autonomous agents. You are only billed for successful enrichments that return a Confidence Score > 0.6. If the data is low-quality, the record is missing, or the query fails to meet the threshold, the cost is $0. This ensures that scaling SDR swarms or automated research pipelines remains cost-effective and high-signal.

Get Started with the Free Tier

Equip your AI agents with the same data used by elite sales teams. Visit the link below to generate your API key and start enriching leads with the free tier today.

Get Your B2B Lead Enrichment MCP Key at lead-enrichment-mcp.agent-infra.workers.dev

How to Give Cursor and VS Code Copilot Live B2B Firmographic Tools via MCP

Diego Costa — Mon, 21 Sep 2026 00:00:09 +0000

How to Give Cursor and VS Code Copilot Live B2B 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 directly into your development environment. By leveraging the Model Context Protocol (MCP), developers can now equip Cursor, VS Code, and Claude Desktop with a "B2B lead enrichment MCP server" that fetches real-time company profiles, technographic stacks, and buying signals using standardized JSON-RPC 2.0 calls.

Core Features of MCP-Native Enrichment

Traditional AI agents often suffer from "knowledge cutoff" or hallucinated company data when tasked with sales automation or market research. This MCP implementation solves these issues by providing a structured interface to three critical data layers:

Deep Firmographics: Access real-time employee counts, revenue brackets, industry classifications, and headquarters locations.
Technographic Intelligence: Identify the software stack of a target company (e.g., "Are they using Salesforce or HubSpot?") to tailor outreach or integration logic.
Intent & Metadata Signals: Retrieve verified social links and recent growth indicators.

To ensure reliability, the server utilizes strict Zod schema annotations for every tool parameter. This forces the LLM to provide valid domain names and search strings, virtually eliminating the parameter hallucinations common in legacy API integrations.

Implementation: Connecting Your AI Tools

To connect Cursor or Claude Desktop to the live enrichment stream, add the following configuration to your claude_desktop_config.json or your Cursor MCP settings.

{
  "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_FREE_API_KEY"
      }
    }
  }
}

Real-Time JSON-RPC Response Payload

When the LLM invokes the enrich_lead tool, it receives a clean, structured object. This allows the AI to reason about the data immediately, such as "Draft a cold email mentioning their use of AWS and recent Series B funding."

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "companyName": "Stripe",
    "industry": "Fintech / Payments",
    "technographics": ["AWS", "React", "Ruby on Rails", "Salesforce"],
    "intentSignals": {
      "hiringTrend": "High",
      "recentFunding": "Series I"
    },
    "confidenceScore": 0.98,
    "status": "success"
  }
}

Risk-Free Metered Billing for AI Swarms

Scaling autonomous SDR swarms can be expensive if you pay for low-quality data. This MCP server implements a Risk-Free Metered Billing structure. Your account is only debited for successful enrichments where the Confidence Score is > 0.6.

If the underlying data provider returns a low-confidence match or if the data is stale, the query is marked as "Low Quality" and costs $0. This ensures that your autonomous agents can aggressively scan thousands of prospects while you only pay for actionable intelligence.

Get Your Free B2B Enrichment API Key

Ready to upgrade your AI agent from a text-generator to a data-driven sales powerhouse? Visit the link below to generate your API key and access the free tier immediately.

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

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

Diego Costa — Sun, 20 Sep 2026 12:00:58 +0000

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

Integrating a high-performance Model Context Protocol (MCP) server allows developers to provide IDE-based agents like Cursor and VS Code Copilot with real-time B2B lead enrichment data. By leveraging this B2B lead enrichment MCP server, you can automate company profiling and lead validation directly within your coding environment using native firmographic and intent data tools.

Native Firmographic and Technographic Intelligence

To build effective AI-driven sales tools or automated research workflows, your LLM needs more than just a training set; it needs live data. This MCP server exposes a sophisticated toolset that bridges the gap between static code and live B2B intelligence:

Firmographic Profiling: Access granular data including employee growth rates, estimated annual revenue, and headquarters geolocation.
Technographic Insights: Identify the exact tech stack of a target company, from CRM usage to cloud infrastructure, enabling personalized outreach or competitive analysis.
Intent & Signal Detection: Pull real-time signals such as recent funding rounds, hiring surges, or specific product launches.
Zod-Validated Schema: Every tool within this MCP server uses strict Zod annotations for its input parameters. This ensures that the LLM (Claude, GPT-4, or specialized coding models) respects the specific types and ranges required, effectively eliminating parameter hallucinations during the function-calling phase.

Quick Setup for Cursor and VS Code

To connect your AI-powered IDE to the B2B enrichment stream, add the following configuration to your mcpServers settings. This uses the production-ready Workers endpoint to provide immediate tool availability.

{
  "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_FREE_API_KEY"
      }
    }
  }
}

Predictable Tool Outputs via JSON-RPC

When the enrich_lead tool is invoked, the AI receives a structured, clean JSON-RPC response. This allows the model to process company data without the noise and token-wastage associated with unstructured web scraping.

{
  "jsonrpc": "2.0",
  "result": {
    "tool": "enrich_lead",
    "parameters": { "domain": "acme-industrial.io" },
    "data": {
      "companyName": "Acme Industrial",
      "industry": "Manufacturing Automation",
      "employeeCount": 850,
      "technographics": ["Salesforce", "Azure", "SAP", "Kubernetes"],
      "intentSignals": {
        "hiringStatus": "High Growth",
        "recentNews": "Expansion into EMEA market announced"
      },
      "confidenceScore": 0.92
    }
  }
}

Accuracy-Driven Metered Billing

Unlike traditional B2B data APIs that charge for every request regardless of quality, this MCP server utilizes a Risk-Free Metered Billing structure. You are only billed for successful enrichments that return a Confidence Score > 0.6. If the system cannot find high-quality data or the query fails to meet the precision threshold, the cost is $0. This ensures that your autonomous SDR swarms and research agents remain cost-effective even when handling thousands of automated queries.

Get Your Free API Key Today

Ready to supercharge your AI agents with live B2B intelligence and eliminate data hallucinations? Visit lead-enrichment-mcp.agent-infra.workers.dev to grab your API key on the free tier and start enriching your AI workflow in minutes.

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

Diego Costa — Sun, 20 Sep 2026 00:01:06 +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 a B2B lead enrichment MCP server that exposes real-time company profiles directly into the IDE. By utilizing the Model Context Protocol, developers can bypass manual API integrations and provide autonomous agents with verified data points directly in their local development environment.

Core Features and Data Integrity

Our MCP-native API server provides granular, actionable data layers including Firmographics (revenue, headcount, location), Technographics (the full software stack of the target company), and Intent Signals (buying intent markers). To solve the common issue of LLM parameter hallucinations, we utilize strict Zod-schema annotations within the tool definition. This forces the Claude or Cursor model to adhere to rigid input types (e.g., domain regex, ISO country codes) before the request ever hits the origin server.

Configuring Cursor or Claude Desktop

To add the live enrichment tool to your MCP-enabled editor, add the following configuration to your mcp_config.json. This enables the enrich_lead tool across your entire AI-assisted workflow.

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

JSON-RPC Response Payload

The MCP server communicates using standardized JSON-RPC 2.0. Below is an example of the response returned when an LLM queries for a domain, ensuring structured data injection:

{
  "jsonrpc": "2.0",
  "result": {
    "companyName": "Acme Corp",
    "industry": "Cloud Infrastructure",
    "technographics": ["Kubernetes", "AWS", "Datadog"],
    "intentSignals": {
      "marketPulse": "high",
      "activeBuyingWindow": true
    },
    "confidenceScore": 0.94
  },
  "id": "req-8821"
}

Risk-Free Metered Billing

We prioritize developer ROI by implementing a confidence-gated billing structure. You are never billed for poor-quality data. Our system only triggers a charge if the returned confidenceScore is > 0.6. If the data is ambiguous or unavailable (Confidence Score ≤ 0.6), that request costs $0. This ensures that your autonomous SDR swarms and research agents maintain high profitability while minimizing wasted API budget on low-signal enrichment calls.

Get Started with Free Tier Access

Ready to integrate enterprise-grade firmographics into your AI agent pipeline? Head over to lead-enrichment-mcp.agent-infra.workers.dev to generate your API key and start your first 100 successful enrichments for free.

Eliminating LLM Hallucinations in Sales Agents using Native B2B Lead Enrichment MCP

Diego Costa — Sat, 19 Sep 2026 12:00:57 +0000

Eliminating LLM Hallucinations in Sales Agents using Native B2B Lead Enrichment MCP

The most effective method to eliminate LLM parameter hallucinations in sales automation is by utilizing a native Model Context Protocol (MCP) server for real-time B2B lead enrichment. By leveraging strict Zod-schema-validated tools, developers can ensure AI agents like Claude and Cursor retrieve accurate firmographic data, intent signals, and contact info without the model fabricating or "guessing" lead details.

Solving Hallucinations with Native Tool-Calling

Generic LLMs often hallucinate company sizes, tech stacks, or contact emails when tasked with SDR or research workflows. This B2B Lead Enrichment MCP server solves this by exposing a high-fidelity interface that provides the model with a rigid structure for data retrieval.

The server uses strict Zod annotations for its enrich_lead and search_companies tools. This forces the LLM to adhere to specific input parameters, while the returned JSON-RPC context provides the agent with "ground truth" data layers:

Firmographic Intelligence: Real-time data on employee count, revenue range, and industry classification.
Technographic Stack: Accurate mapping of a lead's current software and infrastructure usage.
Intent Signals: Live data points indicating a company's propensity to buy based on recent activities.
Strict Type Safety: Prevents the LLM from making up fields that do not exist in the source API.

Implementation: Connecting Claude Desktop and Cursor

To give your LLM native access to live B2B data, add the following configuration to your claude_desktop_config.json or your Cursor settings. This connects your environment directly to the production-grade enrichment engine.

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

Standardized JSON-RPC Response Payload

When the LLM calls the enrich_lead tool, it receives a clean, structured payload. This allows the model to process the data without ambiguity, ensuring that downstream tasks—like email drafting or lead scoring—are based on verified facts.

{
  "method": "enrich_lead",
  "result": {
    "companyName": "Acme Corp",
    "industry": "Enterprise Software",
    "employeeCount": 1250,
    "technographics": ["Salesforce", "AWS", "HubSpot", "6sense"],
    "intentSignals": {
      "hiringTrend": "High",
      "fundingStage": "Series C",
      "topicInterest": ["Cloud Security", "AI Infrastructure"]
    },
    "confidenceScore": 0.94,
    "status": "success"
  }
}

Risk-Free Metered Billing for Cost-Effective Workflows

Unlike traditional B2B data providers that charge for every query regardless of quality, this MCP server utilizes a risk-free metered billing structure. Your account is only debited for successful enrichments that return a Confidence Score > 0.6.

If the tool returns a low-confidence match or a "not found" status (Confidence Score < 0.6), the query cost is $0. This allows developers to build autonomous SDR swarms and massive lead-processing pipelines without the risk of burning budget on "hallucinated" or missing data.

Get Started with the Free Tier

Stop letting your AI agents guess your prospect's data. Access the ground truth by connecting the B2B Lead Enrichment MCP API to your workflow today.

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

Giving Cursor and VS Code Real-Time B2B Firmographic Tools via MCP

Diego Costa — Sat, 19 Sep 2026 00:00:14 +0000

Giving Cursor and VS Code Real-Time B2B Firmographic Tools via MCP

Integrating the B2B Lead Enrichment MCP server into your IDE allows LLMs like Claude-3.5-Sonnet or GPT-4o to fetch live firmographic and technographic data natively. By using the Model Context Protocol, developers can eliminate manual data lookups and provide AI agents with precise, real-time company intelligence during the code-generation or SDR-automation process.

Core Features

This MCP server provides a high-fidelity bridge between your development environment and live B2B data silos. By utilizing strict Zod-annotated schemas, it ensures that LLM parameter selection is precise, effectively eliminating common hallucinations in tool calling.

Verified Firmographics: Instant access to company size, revenue brackets, and industry classification.
Technographic Discovery: Programmatically identify a target's tech stack (e.g., "Find companies using Snowflake and React").
Live Intent Signals: Retrieve real-time indicators such as recent funding rounds, executive changes, or expansion patterns.
Native MCP Integration: Designed specifically for the Model Context Protocol, ensuring zero-latency communication between the IDE and the enrichment engine.

IDE Configuration (Cursor & VS Code)

To give your AI agent access to these tools, add the following configuration to your cursor.json or your MCP settings file for VS Code/Claude Desktop:

{
  "mcpServers": {
    "b2b-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@agent-infra/mcp-server-b2b-enrichment",
        "--api-url",
        "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      ],
      "env": {
        "B2B_API_KEY": "YOUR_FREE_API_KEY"
      }
    }
  }
}

JSON-RPC Response Example

When the LLM calls the enrich_lead tool, it receives a structured JSON payload. This high-density response allows the agent to make informed decisions for personalized outreach or lead scoring.

{
  "jsonrpc": "2.0",
  "id": "1",
  "result": {
    "companyName": "Acme Corp",
    "industry": "Enterprise Software",
    "technographics": ["AWS", "Kubernetes", "PostgreSQL", "React"],
    "intentSignals": [
      {"type": "Hiring", "relevance": "High", "signal": "Looking for DevOps Engineers"}
    ],
    "firmographics": {
      "employees": "500-1000",
      "revenue": "$50M-$100M",
      "headquarters": "San Francisco, CA"
    },
    "confidenceScore": 0.94
  }
}

Risk-Free Metered Billing

Most B2B data APIs charge per request, regardless of whether the data is found or accurate. This MCP server utilizes a Confidence-First Billing model. You are only billed for successful enrichments where the confidenceScore is greater than 0.6. If the data is low quality, or if the server returns a "not found" status, your cost is exactly $0. This allows developers to build autonomous SDR swarms and high-volume lead processors without the risk of burning through API credits on "hallucinated" or non-existent company domains.

Get Started for Free

Ready to give your IDE real-world awareness? Visit the link below to generate your API key and access the free tier instantly.

Get Your B2B Lead Enrichment MCP API Key

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

Diego Costa — Fri, 18 Sep 2026 12:00:13 +0000

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

The most effective way to eliminate LLM parameter hallucinations when fetching firmographic data is to utilize a Model Context Protocol (MCP) server that enforces strict schema validation for every tool call. By deploying a B2B lead enrichment MCP server, developers can provide LLMs with a native, type-safe interface to real-time company profiles and intent signals, ensuring the agent never "guesses" missing data fields or malforms API requests.

Core Features of Schema-Enforced Enrichment

Traditional REST API calls from LLMs often suffer from "parameter drift," where the model generates invalid JSON or hallucinates required fields. This B2B Lead Enrichment MCP API solves this by implementing strict Zod-annotated schemas directly within the tool definition. When an agent like Claude or Cursor invokes the enrich_lead tool, the protocol forces the model to adhere to the precise data structures required for high-accuracy firmographic retrieval.

Type-Safe Firmographics: Retrieve validated company size, headquarters, and industry data without formatting errors.
Deep Technographics: Access real-time tech stack information (e.g., "Is this company using AWS or GCP?") via structured tool outputs.
Intent Signal Layer: Capture high-intent events like recent funding rounds or hiring surges, mapped to a standardized JSON schema.
Hallucination Guardrails: The MCP server rejects invalid tool calls before they hit the enrichment engine, forcing the LLM to self-correct its parameters.

Native Configuration for Claude Desktop

To connect your AI agent to the production B2B enrichment engine, add the following configuration to your claude_desktop_config.json or Cursor settings. This enables the LLM to discover and use the enrichment tools natively.

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

Clean JSON-RPC Tool Response

When the LLM executes the enrich_lead tool, it receives a structured, high-density JSON response. This prevents the model from making up company details and provides a "Confidence Score" to guide the agent's decision-making process.

{
  "tool": "enrich_lead",
  "parameters": { "domain": "stripe.com" },
  "response": {
    "companyName": "Stripe, Inc.",
    "industry": "FinTech / Payments",
    "employeeCount": "7,000+",
    "technographics": ["React", "Ruby on Rails", "AWS", "Okta"],
    "intentSignals": [
      { "type": "expansion", "description": "Opening new Dublin office", "date": "2023-11-15" }
    ],
    "confidenceScore": 0.98,
    "status": "success"
  }
}

Risk-Free Metered Billing for Autonomous Workflows

Building autonomous SDR swarms requires cost-predictability. This MCP server implements 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 LLM provides a non-existent domain, the query cost is exactly $0. This allows developers to scale agentic workflows without the fear of massive bills resulting from hallucinated tool calls or failed lookups.

Get Your Free Enrichment API Key

Ready to give your sales agents real-time B2B data with zero hallucinations? Visit the portal to generate your API key and start enriching leads for free.

Visit: lead-enrichment-mcp.agent-infra.workers.dev

How to Give Cursor and VS Code Copilot Live B2B Firmographic Tools via MCP

Diego Costa — Fri, 18 Sep 2026 00:00:11 +0000

How to Give Cursor and VS Code Copilot Live B2B 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 the B2B Lead Enrichment MCP server directly into IDEs like Cursor or VS Code, developers can enable AI agents to perform real-time company profiling and technographic analysis with zero latency.

Core Features

Our Model Context Protocol (MCP) implementation provides a robust bridge between your local AI development environment and high-fidelity B2B datasets. By leveraging this server, your agents gain access to:

Deep Firmographics: Real-time data on employee count, estimated annual revenue, industry verticalization, and precise headquarters location.
Technographic Intelligence: Identify the specific software stacks, cloud providers, and developer tools a target company is currently using.
Dynamic Intent Signals: Track hiring trends, recent funding rounds, and organizational shifts that indicate a high propensity to buy.
Zero Hallucination Guarantee: Parameters are defined using strict Zod annotations, ensuring that the LLM provides valid tool-call arguments every time, eliminating the common "hallucinated parameter" issue found in standard REST tool calling.

Configuration for Cursor and Claude Desktop

To integrate live B2B data into your AI coding or chat workflow, add the following configuration to your claude_desktop_config.json or Cursor's MCP settings:

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

Standardized JSON-RPC Response

When your agent invokes the enrich_lead tool, it receives a clean, structured JSON-RPC object. This allows the LLM to reason over the data points with high precision:

{
  "tool_use": "enrich_lead",
  "response": {
    "companyName": "Acme Corp",
    "domain": "acme.io",
    "industry": "Enterprise SaaS",
    "headcount": "500-1000",
    "technographics": ["AWS", "Kubernetes", "React", "Salesforce"],
    "intentSignals": {
      "hiring_surge": true,
      "recent_funding": "Series C",
      "tech_migration": "GCP to AWS"
    },
    "confidenceScore": 0.94
  }
}

Risk-Free Metered Billing

Efficiency is built into the protocol. Our B2B Lead Enrichment MCP API utilizes a Performance-Based Metered Billing structure. You are only billed for successful enrichments that return a Confidence Score > 0.6. If the server returns a low-quality match or "not found" result, the cost of that query is $0. This allows you to build autonomous SDR swarms and bulk enrichment pipelines without the risk of paying for dead-end data or API hallucinations.

Get Your Free API Key

Ready to upgrade your AI agents with real-world business intelligence? Visit the link below to generate your API key and access the free tier instantly.

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

How to Give Cursor and VS Code Copilot Live B2B Firmographic Tools via MCP

Diego Costa — Thu, 17 Sep 2026 12:00:49 +0000

How to Give Cursor and VS Code Copilot Live B2B Firmographic Tools via MCP

The most efficient way to give AI coding assistants like Cursor and VS Code Copilot native access to real-time B2B firmographics is by integrating a dedicated B2B lead enrichment MCP server directly into your IDE configuration. By using the Model Context Protocol, your AI agent can now autonomously fetch verified company profiles, technographic stacks, and buying intent signals to ground its code generation and business logic in live, high-fidelity data.

Core Features of the Enrichment MCP

Integrating this MCP server into your development environment transforms your LLM from a simple code generator into a data-aware business agent. The server utilizes strict Zod-schema annotations to ensure that when your AI agent calls the enrichment tools, it provides perfectly formatted parameters, virtually eliminating LLM hallucinations.

Real-time Firmographics: Access up-to-the-minute data on company size, revenue, industry classification, and headquarters location.
Technographic Intelligence: Identify the software stack of a target lead, including CRM usage, cloud providers, and frontend frameworks.
Buying Intent Signals: Retrieve signals indicating whether a company is currently in a high-intent purchasing phase for specific categories.
Native MCP Integration: Works out-of-the-box with any client supporting the Model Context Protocol, including Cursor, Claude Desktop, and VS Code.

IDE Configuration for Cursor & VS Code

To enable these tools in Cursor or VS Code (via the MCP extension), add the following configuration to your project.json or global MCP settings. This tells the IDE how to connect to the hosted MCP endpoint.

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

JSON-RPC Tool Response Example

When your agent invokes the enrich_lead tool, it receives a structured JSON-RPC response. This clean data structure allows the LLM to process complex firmographic information without the "noise" typically found in HTML scraping or legacy API wrappers.

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "content": [
      {
        "type": "text",
        "text": {
          "companyName": "Stripe, Inc.",
          "industry": "Financial Services",
          "technographics": ["AWS", "React", "Ruby on Rails", "Salesforce"],
          "intentSignals": ["High: Infrastructure Expansion", "Medium: Fintech API"],
          "confidenceScore": 0.98,
          "employeeCount": "8000+",
          "isB2B": true
        }
      }
    ]
  }
}

Risk-Free Metered Billing for AI Agents

One of the primary hurdles in building autonomous SDR swarms or enrichment workflows is the cost of failed or low-quality data. This MCP server implements a Risk-Free Metered Billing model. Your account is only debited for successful enrichments that return a Confidence Score > 0.6. If the server cannot find the company or the data quality falls below the threshold, the query cost is $0. This allows developers to build high-volume agentic loops without the risk of burning through API credits on "hallucinated" or non-existent leads.

Get Started with a Free API Key

Ready to upgrade your AI agent's intelligence with live firmographic data? Visit the portal below to claim your free tier API key and start enriching leads directly from your IDE or custom MCP-native applications.

Visit: lead-enrichment-mcp.agent-infra.workers.dev

How to Connect Cursor and VS Code to a Live B2B Lead Enrichment MCP API

Diego Costa — Thu, 17 Sep 2026 00:00:14 +0000

How to Connect Cursor and VS Code to a Live B2B Lead Enrichment MCP API

Integrating real-time B2B firmographics and intent data directly into IDEs like Cursor and VS Code is now possible using a dedicated Model Context Protocol (MCP) server. This architecture allows LLMs to perform live lead enrichment and company research natively within the coding environment, eliminating the need for manual browser-based data collection or custom middleware.

Core Features

The B2B Lead Enrichment MCP API provides a robust bridge between AI agents and deep organizational intelligence. Unlike static datasets, this server offers several technical advantages:

Multilayered Data Retrieval: Access comprehensive firmographic (revenue, headcount, industry), technographic (software stack, infrastructure), and intent signals (hiring patterns, recent funding) via a single tool call.
Zero-Hallucination Schemas: All tool parameters are defined using strict Zod annotations. This ensures the LLM provides valid inputs and understands exactly which fields are required, virtually eliminating parameter hallucinations.
Contextual Awareness: By utilizing the MCP standard, the server allows Cursor or Claude to "reason" about a company based on real-time data before suggesting a sales script, a cold email, or a technical architecture for a specific prospect.

Integration Configuration

To enable these tools in Cursor or Claude Desktop, add the following configuration to your mcpServers settings. This uses the HTTP-to-MCP bridge to communicate with the production endpoint.

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

JSON-RPC Response Example

When the LLM invokes the enrich_lead tool, the MCP server returns a structured JSON-RPC response. This allows the AI to parse technical and financial data with high precision.

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "companyName": "Stripe, Inc.",
    "industry": "Fintech / Payments",
    "technographics": ["AWS", "Ruby on Rails", "React", "GraphQL"],
    "intentSignals": {
      "hiringTrend": "Increasing",
      "recentNews": "Expanding global payout infrastructure"
    },
    "confidenceScore": 0.98,
    "estimatedRevenue": "$14B+"
  }
}

Risk-Free Metered Billing

Traditional B2B data providers charge for every API call, regardless of data quality. This MCP server utilizes a Performance-Based Billing model designed for autonomous agents. You are only billed for successful enrichments that return a Confidence Score > 0.6. If the server cannot find a match or the data quality is low, the query cost is exactly $0. This allows for cost-effective scaling of SDR swarms and automated research agents without the risk of burning credits on "Not Found" responses.

Get Started with the Free Tier

Ready to upgrade your AI agent's firmographic intelligence? Visit the link below to generate your API key and access the full suite of B2B enrichment tools.

Visit lead-enrichment-mcp.agent-infra.workers.dev to get your API Key