Stop Building MCP Servers From Scratch

Every time you want to connect an API to your AI agent, you write another MCP server wrapper. GitHub integration? Custom server. Slack functionality? Another server. Notion access? Yet another server.

You know there's a better way.

MCP Link converts any OpenAPI v3 specification into a fully functional MCP server - automatically mapping every endpoint, parameter, and authentication method without touching your original API code.

The Real Problem

You're building the same boilerplate over and over:

• Manual endpoint mapping for each API operation
• Custom authentication handling for different providers
• Incomplete coverage because manual implementations miss edge cases
• Hours spent on integration code instead of your actual application logic

Meanwhile, thousands of well-documented APIs already exist with OpenAPI specs - from GitHub and Slack to your internal microservices.

What MCP Link Actually Does

Point it at any OpenAPI spec and get a production-ready MCP server:

# Convert GitHub's API in seconds
go run main.go serve --port 8080 &
# Now GitHub's entire API is available to your AI agent

Or use the hosted version instantly:

{
  "mcpServers": {
    "github": {
      "url": "https://mcp-link.vercel.app/links/github"
    }
  }
}

Your AI agent now has complete GitHub access - repositories, issues, pull requests, everything - with zero custom code.

Real Productivity Gains

Instead of 2-3 days per API integration, you get:

• 30 seconds to convert any OpenAPI spec to MCP
• Complete API coverage - every endpoint, not just the ones you manually implemented
• Built-in authentication handling for Bearer tokens, API keys, and custom headers
• Advanced filtering to expose only the endpoints you need: +/users/*:GET;-/internal/**

Concrete Use Cases

Internal Tool Integration: Your company has 12 microservices with OpenAPI specs. Instead of writing 12 MCP servers, run one MCP Link instance that converts them all.

Multi-API Workflows: Build an AI agent that creates GitHub issues from Slack messages, updates Notion databases, and sends status updates - using pre-built API integrations instead of custom wrappers.

Rapid Prototyping: Test AI agent interactions with any public API immediately. Want to experiment with Stripe's API? Point MCP Link at their OpenAPI spec and start building.

Legacy API Modernization: Your older REST APIs get instant AI agent compatibility without modifying existing code - just generate or update their OpenAPI specs.

Integration Reality

MCP Link runs as a standard HTTP server that speaks MCP protocol. Your existing AI agent setup works unchanged:

{
  "mcpServers": {
    "internal-apis": {
      "url": "http://localhost:8080/sse?s=./internal-api.yaml&u=https://api.internal.com&h=Authorization:Bearer"
    }
  }
}

The server handles all the protocol translation, authentication forwarding, and error handling. Your agent sees clean MCP tool calls; your API sees normal REST requests.

Why This Approach Works

OpenAPI specs already contain everything needed for AI integration:

• Complete endpoint definitions with parameters and responses
• Authentication requirements and schemes
• Request/response schemas for proper validation
• Human-readable descriptions for AI understanding

MCP Link reads these specs and generates the MCP interface automatically, ensuring nothing gets missed and everything stays in sync when APIs evolve.

Ready to stop building the same integration code repeatedly? Clone the repo and point it at your first OpenAPI spec - you'll have a working MCP server before your coffee gets cold.