DEV Community: curatedmcp

Salesforce MCP: Give Claude Direct Access to Your CRM

curatedmcp — Sun, 12 Jul 2026 10:55:22 +0000

Salesforce MCP: Give Claude Direct Access to Your CRM

The official Salesforce MCP server turns Claude into a CRM agent. Instead of bouncing between Salesforce, Slack, and email, you can now query records, create deals, pull Einstein AI insights, and manage your entire sales pipeline through natural language in Claude or your IDE.

What It Does

Salesforce MCP is an OAuth-authenticated bridge that grants AI agents granular access to your Salesforce org. It ships with 20+ tools covering the full CRM lifecycle:

Search & retrieve any Salesforce object — Accounts, Contacts, Opportunities, Cases, custom objects
Create and update records across standard and custom fields
Run SOQL queries for complex data retrieval without leaving Claude
Access Einstein AI predictions and insights baked into your data
Manage pipeline — view forecasts, update stages, handle approvals
Pull reports and dashboards — render them interactively in Claude's chat window
Track activity — view email history, task logs, and engagement data

Because it's OAuth-authenticated with Salesforce permission sets, your agent respects the same access controls as your team. It works with Enterprise, Unlimited, and Developer editions.

How to Install

npx -y @salesforce/mcp

Add it to your Claude Desktop config:

{
  "mcpServers": {
    "salesforce-mcp": {
      "command": "npx -y @salesforce/mcp"
    }
  }
}

You'll be prompted to authenticate with your Salesforce org on first run.

Real-World Use Cases

Morning standup in Claude — "Summarize my pipeline for Q1: show all opportunities in negotiation stage, their win probability from Einstein, and which ones have no activity in the last week."
Lead triage in Cursor — "Create a contact from this email, auto-match it to an existing Account, and move the related lead to 'qualified' with a summary of the company research I just did."
Deal intelligence — "Pull all closed-won deals from the last 90 days with deal size, sales rep, and close date. What's the average sales cycle by industry?"

Full install guides for Claude Desktop, Cursor, Windsurf, and more at CuratedMCP.

Hugging Face MCP: Search, Run, and Deploy 500k+ AI Models Directly from Your Agent

curatedmcp — Sat, 11 Jul 2026 10:38:10 +0000

Hugging Face MCP: Search, Run, and Deploy 500k+ AI Models Directly from Your Agent

The Hugging Face MCP server connects your AI agent directly to the world's largest open-source AI model repository. Instead of switching tabs between Claude and the Hugging Face Hub, you can now search models, run inference, access datasets, and deploy Spaces entirely through conversation — making it dramatically faster to prototype with cutting-edge open-source models.

What It Does

This server unlocks full programmatic access to Hugging Face's ecosystem. Your AI agent can:

Search intelligently across 500,000+ models filtered by task (NLP, vision, audio), framework (PyTorch, TensorFlow), and performance metrics
Run inference on any model via the Inference API without local hardware
Access 150,000+ datasets with schema inspection and preview capabilities
Manage Spaces — deploy, update, and share interactive Gradio/Streamlit applications
Compare performance using the Open LLM Leaderboard and community benchmarks
Download weights and configs for fine-tuning or local deployment

If you're building with open-source models, this eliminates friction. No more copy-pasting model IDs or manually checking dataset schemas. Your agent becomes a Hugging Face power user.

How to Install

npx -y @huggingface/mcp

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "hugging-face-mcp": {
      "command": "npx -y @huggingface/mcp"
    }
  }
}

See the official documentation for Cursor, Windsurf, and advanced setup options.

Real-World Use Cases

Model Search & Evaluation: "Find me the best open-source sentiment analysis model under 1B parameters with recent updates. Show me the benchmarks and community discussions."
Inference on Demand: "Run this customer feedback through Mistral-7B and give me the top 3 themes." No local GPU required — inference happens via API.
Dataset Discovery: "What datasets exist for training a code completion model? Show me the schema and a sample of rows."

Full install guides for Claude Desktop, Cursor, Windsurf, and more at CuratedMCP.

Exa MCP: Semantic search for AI agents that actually understands what you're looking for

curatedmcp — Fri, 10 Jul 2026 10:38:08 +0000

Exa MCP: Semantic search for AI agents that actually understands what you're looking for

Traditional keyword search is dead weight for AI workflows. Exa MCP connects your Claude, Cursor, or Windsurf agent to neural search — meaning your AI can find conceptually related content, research papers by similarity, and discover competitors doing the same thing as your target company, even without keyword overlap.

This is the search layer for research-intensive AI tasks. Exa understands meaning. It filters by date. It knows academic papers from GitHub repos from news articles. Your agent stops guessing keyword combinations and starts finding what actually matters.

What It Does

Exa MCP gives your AI agent a search engine built for semantic understanding, not keyword matching. Instead of phrase-matching, it finds content by concept — so a query like "companies doing Figma but for 3D modeling" actually returns relevant startups, not just pages mentioning those words together.

Key capabilities:

Neural search: Find content by meaning across the entire web
Similarity matching: "Show me papers like this arXiv abstract" — instant conceptual discovery
Research mode: Multi-source synthesis for comprehensive answers
Temporal precision: Filter results to specific date ranges (find what was written before 2023)
Domain targeting: Search academic papers, GitHub repos, news, or technical docs specifically
Structured extraction: Get highlighted passages and clean content, not just links

For developers, this unlocks AI agents that can actually do research, competitive analysis, and discovery without you hand-crafting search queries.

How to Install

npx -y exa-mcp-server

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "exa-mcp": {
      "command": "npx -y exa-mcp-server"
    }
  }
}

Grab your free Exa API key at exa.ai, set it as an environment variable, and you're live.

Real-World Use Cases

Competitor research: Ask Claude to find companies building AI-powered design tools like Figma, get semantically matched results instead of keyword noise
Research synthesis: "Find academic papers on federated learning from the last two years, then summarize the consensus" — your agent pulls relevant papers and synthesizes findings
Documentation discovery: Help Cursor find implementation examples across GitHub and technical blogs without exact keyword matches — find the pattern, not the phrase

Full install guides for Claude Desktop, Cursor, Windsurf, and more at CuratedMCP.

Cloudinary MCP: Give Claude Direct Access to Your Media Pipeline

curatedmcp — Thu, 09 Jul 2026 10:38:07 +0000

Cloudinary MCP: Give Claude Direct Access to Your Media Pipeline

The Cloudinary MCP server connects AI agents like Claude and Cursor directly to your media management workflow. Instead of describing image transformations or manually handling asset uploads, you can now ask Claude to do it—resize product photos, convert formats, remove backgrounds, analyze content, and generate optimized delivery URLs all through natural language commands.

This is the official Cloudinary integration, meaning it has full API access to the platform's transformation engine, CDN, and AI-powered features. For teams managing hundreds or thousands of media assets, this cuts manual work significantly.

What It Does

Cloudinary MCP unlocks four core capabilities:

Upload & Manage: Send images or videos directly from URLs or file paths into your Cloudinary account. Organize them into folders and tag them for later retrieval.

Transform & Optimize: Resize, crop, format-convert, and quality-compress images on the fly. Ask Claude to "convert all PNGs to WebP at 80% quality" and it handles the batch job.

AI-Powered Analysis: Leverage Cloudinary's background removal, object detection, and content analysis. Claude can identify what's in an image and auto-generate alt text.

Generate Delivery URLs: Get responsive image URLs for different breakpoints or CDN-optimized links with transformations baked in—perfect for web and mobile workflows.

This works because Claude can parse Cloudinary's API responses and chain commands together. You ask once; the agent figures out the steps.

How to Install

Install via npm:

npx -y cloudinary-mcp-server

Then configure for Claude Desktop by adding this to your claude_desktop_config.json:

{
  "mcpServers": {
    "cloudinary-mcp": {
      "command": "npx -y cloudinary-mcp-server",
      "env": {
        "CLOUDINARY_CLOUD_NAME": "your_cloud_name",
        "CLOUDINARY_API_KEY": "your_api_key",
        "CLOUDINARY_API_SECRET": "your_api_secret"
      }
    }
  }
}

Get your credentials from your Cloudinary dashboard.

Real-World Use Cases

E-commerce workflows: Upload a product image, auto-generate responsive sizes for mobile/tablet/desktop, and get CDN URLs in one Claude prompt.
Batch media processing: "Remove backgrounds from all 50 product photos in my /catalog folder and convert them to PNG."
Content analysis: "What objects are in these 10 images? Generate alt text for each."

Cloudinary powers 2 million developers and companies like Fiverr, TED, and The Guardian. The MCP server is free to use with your existing Cloudinary account (free tier available).

Full install guides for Claude Desktop, Cursor, Windsurf, and more at CuratedMCP.

Upstash MCP: Give Claude Direct Access to Serverless Redis and Kafka

curatedmcp — Wed, 08 Jul 2026 10:38:07 +0000

Upstash MCP: Give Claude Direct Access to Serverless Redis and Kafka

Managing caches, rate limits, and message queues shouldn't require context-switching out of your AI agent. Upstash MCP bridges that gap by giving Claude, Cursor, and Windsurf direct access to Upstash's serverless Redis and Kafka services — all through a single, unified interface.

What It Does

Upstash MCP unlocks two core capabilities for AI agents:

Redis operations: Get, set, and delete keys with full TTL support. Work with strings, lists, hashes, sets, and sorted sets. Inspect key patterns, check database statistics, and manage multiple databases across regions — all without leaving your agent's context.

Kafka management: Create and manage topics, inspect consumer group lag, and monitor message throughput directly from Claude.

This is particularly valuable if you're already using Context7 MCP (Upstash's documentation layer) — now you can manage the Redis cache powering it directly from your agent. The pay-per-request pricing model means zero idle costs, making it perfect for intermittent AI workloads that don't justify always-on infrastructure.

How to Install

Install via npm:

npx -y @upstash/mcp-server

Add to your Claude Desktop claude_desktop_config.json:

{
  "mcpServers": {
    "upstash-mcp": {
      "command": "npx -y @upstash/mcp-server",
      "env": {
        "UPSTASH_REDIS_REST_URL": "your-redis-url",
        "UPSTASH_REDIS_REST_TOKEN": "your-redis-token",
        "UPSTASH_KAFKA_REST_URL": "your-kafka-url",
        "UPSTASH_KAFKA_REST_TOKEN": "your-kafka-token"
      }
    }
  }
}

Get credentials from your Upstash console.

Real-World Use Cases

Cache inspection during debugging: Ask Claude to check what's currently cached, inspect TTLs, and clear specific keys without SSH-ing into infrastructure.
Rate limit management: Have your agent adjust rate-limit counters in Redis or check current thresholds while troubleshooting API behavior.
Event queue monitoring: Query Kafka consumer lag, topic throughput, and message rates to diagnose streaming pipeline issues in real time.

Full install guides for Claude Desktop, Cursor, Windsurf, and more at CuratedMCP.

PlanetScale MCP: Deploy Schema Changes Without Downtime via AI

curatedmcp — Tue, 07 Jul 2026 10:38:07 +0000

PlanetScale MCP: Deploy Schema Changes Without Downtime via AI

PlanetScale MCP connects your AI agents directly to PlanetScale's serverless MySQL platform, unlocking a workflow that's been impossible with traditional databases: propose schema changes, test them in isolated branches, and deploy to production with zero downtime.

Whether you're using Claude, Cursor, or Windsurf, this server gives your AI agent full control over database operations—from executing queries to managing the branching and deploy request system that makes PlanetScale unique. It's the database layer your AI agent was missing.

What It Does

PlanetScale MCP exposes core database operations as tools your AI can invoke:

Execute queries across any of your PlanetScale databases
Create and manage branches for safe, isolated schema changes
Open deploy requests to safely migrate schema changes to production without blocking reads or writes
Monitor performance with query insights and slow query analysis
Manage credentials securely—connection strings, passwords, and access controls
Inspect deployments with rollback capabilities if something goes wrong
Analyze cache performance on Boost-enabled databases
Handle data migrations and imports

The killer feature: your AI can now propose a schema migration, create a branch to test it, validate the change works, and open a deploy request—all without you writing a single migration script or worrying about downtime. It's VCS for your database.

How to Install

npx -y @planetscale/mcp

Add to your Claude Desktop config:

{
  "mcpServers": {
    "planetscale-mcp": {
      "command": "npx -y @planetscale/mcp"
    }
  }
}

Authenticate with your PlanetScale service token. Full setup instructions are in the PlanetScale MCP docs.

Real-World Use Cases

Rapid feature development: Ask Claude to add a new column to your schema, test it in a branch, and automatically open a deploy request—no manual SQL scripts required.
Performance optimization: Have your AI analyze slow queries from Insights, propose index changes, test them in isolation, and deploy safe improvements.
Data migrations at scale: Let your agent handle imports and migrations across branches while your production database stays live and serving traffic.

Full install guides for Claude Desktop, Cursor, Windsurf, and more at CuratedMCP.

MCP Ecosystem Week 28: Cross-IDE Standardization Now Matters—Here's Why Your Allowlist Needs It

curatedmcp — Mon, 06 Jul 2026 10:38:18 +0000

MCP Ecosystem Week 28: Cross-IDE Standardization Now Matters—Here's Why Your Allowlist Needs It

The MCP ecosystem is fragmenting faster than most platform teams can track. This week's data reveals a critical shift: developers are standardizing on a small set of high-utility servers—GitHub, OpenAI, Figma, Anthropic Claude—but they're running them across four different AI coding environments (Claude Code, Cursor, Windsurf, GitHub Copilot). That means your allowlist policy isn't just about which servers you approve; it's about ensuring they work identically wherever your team uses them. One new server this week underscores exactly that challenge.

This Week in MCP

We added one new risk-classified server to the catalog:

threadctx-mcp — A shared memory server for AI coding agents. The governance signal here is straightforward: threadctx-mcp runs identically in Claude Code and Cursor without config drift. If your team uses both IDEs (and most do), this is a candidate for your core allowlist. No authentication, no external data connectors, minimal supply-chain risk. The decision tree: Does your team need persistent conversation state across coding sessions? If yes, test in a pilot group before rolling out. If no, block it to reduce agent complexity.

The catalog now holds 74 risk-classified servers—all free tier, zero paid MCP dependencies emerging this week. That's a quiet win for cost transparency, but the real governance challenge isn't cost; it's velocity. Your developers see these servers in the marketplace and ask to use them. Your allowlist either keeps pace or becomes a friction point that drives shadow MCP adoption.

On the Radar

Five servers dominated developer attention this week:

GitHub Copilot MCP (98k views) — Direct integration of GitHub's code intelligence. Governance consideration: does your org allow Copilot's use of private repo data? This server surfaces that question immediately.
OpenAI MCP (87k views) — GPT-4o, DALL-E, Whisper, and Embeddings. Red flag: token spend attribution. If you're not logging calls through this server, you won't see third-party model costs on your bill.
Figma MCP (82k views) — Design system access. Auth model: typically OAuth to Figma workspace. Ensure your IT team has audited the token scope before allowlisting.
GitHub MCP (76k views) — Repo and workflow management. High leverage, high risk if approval flows are weak; a misconfigured agent could merge unapproved PRs.
Anthropic Claude MCP (76k views) — Claude-as-sub-agent. Nested model calls multiply token spend and latency; if you're measuring Claude spend, this one needs per-call observability.

All five are high-signal, high-touch. None should be allowlisted without a risk review specific to your org's auth model, data classification, and audit posture.

Governance Take

Here's the hard truth: most platform teams have an allowlist for one AI coding environment and assume it applies everywhere. It doesn't. Cursor reads from one config file. Claude Code reads from another. GitHub Copilot doesn't read allowlists at all—it respects org-level policy, but that's coarse-grained. Windsurf has its own model. Result: developers end up running different MCP stacks on different machines, and your central audit log has blind spots.

Start here: inventory which MCP servers are actually running across your four main IDEs this week. Don't assume you know. Use machine-level telemetry if you have it, or run a voluntary audit sweep. Then pick your five highest-leverage servers (GitHub, Anthropic Claude, OpenAI is a safe trio) and enforce the same risk classification across all four IDEs. Document the exceptions. Use TokenShield to build a live spend ledger by IDE and server, so when someone asks "why is our Claude spend up 40%?" you can trace it to a specific server and a specific cohort of developers.

The teams winning at this aren't trying to block everything; they're winning by knowing what's running and keeping the allowlist synchronized. That's governance at scale.

Govern MCP usage across your team with CuratedMCP — or scan your own stack free at https://www.curatedmcp.com/auditor.

Datadog MCP: Let Claude Debug Your Stack in Real Time

curatedmcp — Mon, 06 Jul 2026 10:38:13 +0000

Datadog MCP: Let Claude Debug Your Stack in Real Time

If you're tired of tab-switching between your code editor, Datadog dashboards, and logs trying to figure out what broke, there's a better way. The official Datadog MCP server connects Claude (or your favorite AI agent) directly to your full observability stack—metrics, logs, traces, and incidents—turning "something is wrong" into "here's why and how to fix it" within the same conversation.

What It Does

Datadog MCP is a Model Context Protocol server that gives AI agents read and write access to your entire observability layer. Query metrics with PromQL/DQL expressions, tail logs in real time, inspect distributed traces and service maps, check monitor status, and pull incident timelines—all programmatically.

The magic is in the workflow: when an alert fires, Claude can autonomously fetch the metric spike, pull correlated logs from the same time window, trace the request across services, and propose a root cause and fix—without you context-switching. You get structured data from your observability platform piped directly into your AI's reasoning loop.

Features include APM service performance queries, infrastructure and host health inspection, synthetic test result analysis, and the ability to create dashboards and widgets on the fly. For teams already invested in Datadog, this eliminates the friction of manual investigation.

How to Install

Install the server via npm:

npx -y @datadog/mcp-server

Then add it to your Claude Desktop configuration:

{
  "mcpServers": {
    "datadog-mcp": {
      "command": "npx -y @datadog/mcp-server",
      "env": {
        "DATADOG_API_KEY": "your_api_key_here",
        "DATADOG_APP_KEY": "your_app_key_here",
        "DATADOG_SITE": "datadoghq.com"
      }
    }
  }
}

Grab your API and app keys from your Datadog account settings. Full setup guides for Cursor and Windsurf are in the docs.

Real-World Use Cases

Incident triage in Claude: Paste an alert into your chat. Claude queries the metric, pulls logs, finds the trace, and hands you a diagnosis and diff—all in one response.
On-call automation in Cursor: Your CI/CD alert hits. Ask Claude to check host health, check related monitors, and suggest scaling actions—all pulling live data from your infrastructure map.
Postmortem data gathering: Generate a timeline of events, correlated logs, and affected services from an incident—Claude assembles the narrative without you hunting through tabs.

Full install guides for Claude Desktop, Cursor, Windsurf, and more at CuratedMCP.

Tavily MCP: Web search built for AI agents, not humans

curatedmcp — Sun, 05 Jul 2026 10:38:06 +0000

Tavily MCP: Web search built for AI agents, not humans

When Claude or Cursor needs to search the web, you don't want raw HTML noise—you want structured, factual results ready for LLM consumption. Tavily MCP bridges that gap.

Tavily is a search API purpose-built for AI agents. Unlike general search engines, it returns clean, parsed content optimized for language models: no ads, no layout markup, no irrelevant cruft. Just the facts, with source citations attached. It's trusted by LangChain, AutoGPT, and thousands of agent builders because it actually understands what an AI needs to reason about the real world.

What It Does

Tavily MCP gives your AI agents real-time web search with source attribution. You get structured results with content previews, publication dates, and URLs—everything your agent needs to ground responses in actual sources.

Control search depth with basic (fast) or advanced (comprehensive) modes. Filter by domain to focus on trusted sources or exclude unreliable ones. Switch to news mode for recent events. Extract raw content from any URL directly. The API returns up to 20 results per query, each with a summary and full citation data.

The key difference: Tavily was built for agents, not humans. The output format, filtering options, and relevancy tuning all assume an LLM on the other end, not a human clicking links.

How to Install

npx -y tavily-mcp

Add to your Claude Desktop config:

{
  "mcpServers": {
    "tavily-mcp": {
      "command": "npx -y tavily-mcp",
      "env": {
        "TAVILY_API_KEY": "your-api-key-here"
      }
    }
  }
}

Real-World Use Cases

Fact-checking in real-time: Ask Claude to verify current market prices, recent news, or live event outcomes without hallucination risk.
Research automation in Cursor: Build a code research tool that searches for library documentation, GitHub issues, and Stack Overflow answers—all with proper citations.
News-driven workflows: Set up alerts or batch jobs that search for recent developments in your industry and summarize findings with sources.

Full install guides for Claude Desktop, Cursor, Windsurf, and more at CuratedMCP.

Neon MCP: Let AI Safely Test and Migrate Your Production Database

curatedmcp — Sat, 04 Jul 2026 10:32:10 +0000

Neon MCP: Let AI Safely Test and Migrate Your Production Database

The Neon MCP server connects Claude, Cursor, and other AI agents directly to Neon's serverless PostgreSQL platform — giving your AI assistant full control over database provisioning, branching, schema inspection, and migrations. It's the official integration, built by Neon's team.

The killer feature here: database branching. Your AI can create an isolated copy of your production database, run destructive operations or complex migrations in that branch, then merge or discard the changes. This makes AI-driven schema changes dramatically safer than running them directly on prod.

What It Does

This MCP server unlocks several powerful capabilities:

Execute raw SQL queries against your Neon databases. Create and manage database branches — isolated, ephemeral copies perfect for testing. Provision new projects and databases instantly via API. Inspect table schemas and relationships so the AI understands your data structure. Run migrations and schema changes safely in branched environments. Monitor compute usage and configure auto-suspend for cost control.

The serverless architecture is particularly useful for AI workflows that run intermittently — you pay zero when the agent isn't active. No idle compute tax.

How to Install

npx -y @neondatabase/mcp-server-neon

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "neon-mcp": {
      "command": "npx -y @neondatabase/mcp-server-neon",
      "env": {
        "NEON_API_KEY": "your_api_key_here"
      }
    }
  }
}

Grab your API key from the Neon console, then restart Claude.

Real-World Use Cases

Automated schema migrations: Ask Claude to refactor your database schema. It creates a branch, runs the migration, validates the result, and reports back—all without touching production.
Data exploration and testing: "Analyze my users table and suggest an index strategy." Claude inspects your schema, runs test queries on a branch, and shows you the performance impact.
Rapid prototyping: Spin up new databases and branches on the fly as part of your development workflow, all from within Claude's conversation interface.

Full install guides for Claude Desktop, Cursor, Windsurf, and more at CuratedMCP.

Firecrawl MCP: Web scraping and autonomous research for AI agents

curatedmcp — Thu, 02 Jul 2026 10:41:19 +0000

Firecrawl MCP: Web scraping and autonomous research for AI agents

Web scraping with Claude just got serious. Firecrawl MCP connects your AI agents to the full web — handling JavaScript-rendered pages, PDFs, entire site crawls, and even autonomous research tasks that would normally require manual browsing.

If you've hit walls with basic fetch tools, this is why: Firecrawl renders JavaScript like a real browser, extracts clean markdown instead of raw HTML, handles anti-bot detection with residential proxies, and returns LLM-optimized output that doesn't waste token budget on noise. It's built for the messy internet, not toy websites.

The standout feature is the Deep Research agent — point it at a topic, and it autonomously researches across multiple sources for hours, returning structured findings. For everything else: single-URL scraping, multi-page crawls with depth control, structured data extraction via custom schemas, PDF parsing, sitemap discovery. All the tools modern web automation actually needs.

What It Does

Firecrawl unlocks two core capabilities for your AI agents:

Web intelligence: Scrape any page to clean markdown, crawl entire websites with filtering, extract structured data using schemas you define, and map site structure automatically. Works on SPAs, paywall-adjacent content, and sites that block simple scrapers.

Autonomous research: Deploy the Deep Research agent to handle multi-hour research tasks independently — perfect for market analysis, competitor tracking, or knowledge synthesis that would kill your token budget if done interactively.

This means Claude and other agents can now access real-time web data, reason about it, and compile findings without you manually copying URLs or parsing HTML.

How to Install

npx -y firecrawl-mcp

Add to your Claude Desktop config:

{
  "mcpServers": {
    "firecrawl-mcp": {
      "command": "npx -y firecrawl-mcp",
      "env": {
        "FIRECRAWL_API_KEY": "your_api_key_here"
      }
    }
  }
}

Grab a free API key at firecrawl.dev — 500 credits/month included.

Real-World Use Cases

Competitive analysis: Crawl competitor pricing pages, product catalogs, or blog archives. Ask Claude to extract pricing tiers, feature comparisons, and publishing cadence in one shot.
Data extraction at scale: Need structured data from 50+ product pages? Define a schema (name, price, rating, stock), hand it to Firecrawl batch scraping, and feed the results back to Claude for synthesis.
Research automation: Ask Claude to research "market sizing for AI testing tools" — the Deep Research agent runs autonomously, gathers findings from multiple sources, and returns a structured report without you touching it.

Full install guides for Claude Desktop, Cursor, Windsurf, and more at CuratedMCP.

Resend MCP: Send transactional emails directly from your AI agent

curatedmcp — Wed, 01 Jul 2026 10:26:49 +0000

Resend MCP: Send transactional emails directly from your AI agent

Building email workflows into AI agents just became frictionless. Resend MCP is the official Model Context Protocol server that gives Claude, Cursor, and other AI tools direct access to Resend's email API—no manual API calls, no context switching.

Instead of writing code to send emails, you can ask your AI agent: "Send a welcome email to users who signed up today" or "Check yesterday's delivery rate." The agent handles template rendering, domain management, audience segmentation, and analytics tracking through natural language.

This is the same email infrastructure trusted by Vercel, Clerk, and thousands of developer teams. Now it's accessible to your AI workflows.

What It Does

Resend MCP unlocks five core capabilities for AI agents:

Send emails — plain text or HTML, with variables and template support
Manage domains — configure sending domains, verify DNS records, and monitor reputation
Track delivery — monitor open rates, click-through rates, bounces, and complaints in real time
Segment audiences — create, update, and manage email lists programmatically
Schedule campaigns — queue emails and access detailed analytics

The server translates these operations into tools your AI agent can invoke conversationally. No SDK wrestling. No boilerplate. Just ask the agent to handle your email logic.

How to Install

Install the Resend MCP server:

npx -y @resend/mcp

Then configure it in your AI tool's settings. For Claude Desktop, add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "resend-mcp": {
      "command": "npx -y @resend/mcp",
      "env": {
        "RESEND_API_KEY": "your_resend_api_key_here"
      }
    }
  }
}

Get your API key from resend.com/api-keys.

Real-World Use Cases

Onboarding automation — "Send a personalized welcome email to all users who signed up in the last 24 hours, then add them to the onboarding-cohort audience segment."
Delivery monitoring — "Pull the analytics for our weekly digest sent yesterday—what's the open rate, and which domains had bounce issues?"
Template management — "Create a password reset email template that uses our brand colors, then test it with a sample recipient."

Full install guides for Claude Desktop, Cursor, Windsurf, and more at CuratedMCP.