Mcp Integration logo

Mcp Integration

OrganizationPopular
anthropics
mcp-integration

This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration.

Overview

Publisheranthropics
Repositoryclaude-plugins-official
Skill namemcp-integration
Stars
36.4K
Forks
4.1K
Bundled files
6
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by anthropics on GitHub. Read the source before you install it.

Installation

Install the Mcp Integration AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/anthropics/claude-plugins-official.git /tmp/claude-plugins-official
mkdir -p .claude/skills
cp -r /tmp/claude-plugins-official/plugins/plugin-dev/skills/mcp-integration .claude/skills/mcp-integration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mcp Integration in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Mcp Integration on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Mcp Integration is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

MCP Integration for Claude Code Plugins

Overview

Model Context Protocol (MCP) enables Claude Code plugins to integrate with external services and APIs by providing structured tool access. Use MCP integration to expose external service capabilities as tools within Claude Code.

Key capabilities:

  • Connect to external services (databases, APIs, file systems)
  • Provide 10+ related tools from a single service
  • Handle OAuth and complex authentication flows
  • Bundle MCP servers with plugins for automatic setup

MCP Server Configuration Methods

Plugins can bundle MCP servers in two ways:

Method 1: Dedicated .mcp.json (Recommended)

Create .mcp.json at plugin root:

json
{
  "database-tools": {
    "command": "${CLAUDE_PLUGIN_ROOT}/servers/db-server",
    "args": ["--config", "${CLAUDE_PLUGIN_ROOT}/config.json"],
    "env": {
      "DB_URL": "${DB_URL}"
    }
  }
}

Benefits:

  • Clear separation of concerns
  • Easier to maintain
  • Better for multiple servers

Method 2: Inline in plugin.json

Add mcpServers field to plugin.json:

json
{
  "name": "my-plugin",
  "version": "1.0.0",
  "mcpServers": {
    "plugin-api": {
      "command": "${CLAUDE_PLUGIN_ROOT}/servers/api-server",
      "args": ["--port", "8080"]
    }
  }
}

Benefits:

  • Single configuration file
  • Good for simple single-server plugins

MCP Server Types

stdio (Local Process)

Execute local MCP servers as child processes. Best for local tools and custom servers.

Configuration:

json
{
  "filesystem": {
    "command": "npx",
    "args": ["-y", "@modelcontextprotocol/server-filesystem", "/allowed/path"],
    "env": {
      "LOG_LEVEL": "debug"
    }
  }
}

Use cases:

  • File system access
  • Local database connections
  • Custom MCP servers
  • NPM-packaged MCP servers

Process management:

  • Claude Code spawns and manages the process
  • Communicates via stdin/stdout
  • Terminates when Claude Code exits

SSE (Server-Sent Events)

Connect to hosted MCP servers with OAuth support. Best for cloud services.

Configuration:

json
{
  "hosted-service": {
    "type": "sse",
    "url": "https://mcp.example.com/sse"
  }
}

Use cases:

  • Official hosted MCP servers (Asana, GitHub, etc.)
  • Cloud services with MCP endpoints
  • OAuth-based authentication
  • No local installation needed

Authentication:

  • OAuth flows handled automatically
  • User prompted on first use
  • Tokens managed by Claude Code

HTTP (REST API)

Connect to RESTful MCP servers with token authentication.

Configuration:

json
{
  "api-service": {
    "type": "http",
    "url": "https://api.example.com/mcp",
    "headers": {
      "Authorization": "Bearer ${API_TOKEN}",
      "X-Custom-Header": "value"
    }
  }
}

Use cases:

  • REST API-based MCP servers
  • Token-based authentication
  • Custom API backends
  • Stateless interactions

WebSocket (Real-time)

Connect to WebSocket MCP servers for real-time bidirectional communication.

Configuration:

json
{
  "realtime-service": {
    "type": "ws",
    "url": "wss://mcp.example.com/ws",
    "headers": {
      "Authorization": "Bearer ${TOKEN}"
    }
  }
}

Use cases:

  • Real-time data streaming
  • Persistent connections
  • Push notifications from server
  • Low-latency requirements

Environment Variable Expansion

All MCP configurations support environment variable substitution:

${CLAUDE_PLUGIN_ROOT} - Plugin directory (always use for portability):

json
{
  "command": "${CLAUDE_PLUGIN_ROOT}/servers/my-server"
}

User environment variables - From user's shell:

json
{
  "env": {
    "API_KEY": "${MY_API_KEY}",
    "DATABASE_URL": "${DB_URL}"
  }
}

Best practice: Document all required environment variables in plugin README.

MCP Tool Naming

When MCP servers provide tools, they're automatically prefixed:

Format: mcp__plugin_<plugin-name>_<server-name>__<tool-name>

Example:

  • Plugin: asana
  • Server: asana
  • Tool: create_task
  • Full name: mcp__plugin_asana_asana__asana_create_task

Using MCP Tools in Commands

Pre-allow specific MCP tools in command frontmatter:

markdown
---
allowed-tools: [
  "mcp__plugin_asana_asana__asana_create_task",
  "mcp__plugin_asana_asana__asana_search_tasks"
]
---

Wildcard (use sparingly):

markdown
---
allowed-tools: ["mcp__plugin_asana_asana__*"]
---

Best practice: Pre-allow specific tools, not wildcards, for security.

Lifecycle Management

Automatic startup:

  • MCP servers start when plugin enables
  • Connection established before first tool use
  • Restart required for configuration changes

Lifecycle:

  1. Plugin loads
  2. MCP configuration parsed
  3. Server process started (stdio) or connection established (SSE/HTTP/WS)
  4. Tools discovered and registered
  5. Tools available as mcp__plugin_...__...

Viewing servers: Use /mcp command to see all servers including plugin-provided ones.

Authentication Patterns

OAuth (SSE/HTTP)

OAuth handled automatically by Claude Code:

json
{
  "type": "sse",
  "url": "https://mcp.example.com/sse"
}

User authenticates in browser on first use. No additional configuration needed.

Token-Based (Headers)

Static or environment variable tokens:

json
{
  "type": "http",
  "url": "https://api.example.com",
  "headers": {
    "Authorization": "Bearer ${API_TOKEN}"
  }
}

Document required environment variables in README.

Environment Variables (stdio)

Pass configuration to MCP server:

json
{
  "command": "python",
  "args": ["-m", "my_mcp_server"],
  "env": {
    "DATABASE_URL": "${DB_URL}",
    "API_KEY": "${API_KEY}",
    "LOG_LEVEL": "info"
  }
}

Integration Patterns

Pattern 1: Simple Tool Wrapper

Commands use MCP tools with user interaction:

markdown
# Command: create-item.md
---
allowed-tools: ["mcp__plugin_name_server__create_item"]
---

Steps:
1. Gather item details from user
2. Use mcp__plugin_name_server__create_item
3. Confirm creation

Use for: Adding validation or preprocessing before MCP calls.

Pattern 2: Autonomous Agent

Agents use MCP tools autonomously:

markdown
# Agent: data-analyzer.md

Analysis Process:
1. Query data via mcp__plugin_db_server__query
2. Process and analyze results
3. Generate insights report

Use for: Multi-step MCP workflows without user interaction.

Pattern 3: Multi-Server Plugin

Integrate multiple MCP servers:

json
{
  "github": {
    "type": "sse",
    "url": "https://mcp.github.com/sse"
  },
  "jira": {
    "type": "sse",
    "url": "https://mcp.jira.com/sse"
  }
}

Use for: Workflows spanning multiple services.

Security Best Practices

Use HTTPS/WSS

Always use secure connections:

json
"url": "https://mcp.example.com/sse"
"url": "http://mcp.example.com/sse"

Token Management

DO:

  • ✅ Use environment variables for tokens
  • ✅ Document required env vars in README
  • ✅ Let OAuth flow handle authentication

DON'T:

  • ❌ Hardcode tokens in configuration
  • ❌ Commit tokens to git
  • ❌ Share tokens in documentation

Permission Scoping

Pre-allow only necessary MCP tools:

markdown
✅ allowed-tools: [
  "mcp__plugin_api_server__read_data",
  "mcp__plugin_api_server__create_item"
]

❌ allowed-tools: ["mcp__plugin_api_server__*"]

Error Handling

Connection Failures

Handle MCP server unavailability:

  • Provide fallback behavior in commands
  • Inform user of connection issues
  • Check server URL and configuration

Tool Call Errors

Handle failed MCP operations:

  • Validate inputs before calling MCP tools
  • Provide clear error messages
  • Check rate limiting and quotas

Configuration Errors

Validate MCP configuration:

  • Test server connectivity during development
  • Validate JSON syntax
  • Check required environment variables

Performance Considerations

Lazy Loading

MCP servers connect on-demand:

  • Not all servers connect at startup
  • First tool use triggers connection
  • Connection pooling managed automatically

Batching

Batch similar requests when possible:

# Good: Single query with filters
tasks = search_tasks(project="X", assignee="me", limit=50)

# Avoid: Many individual queries
for id in task_ids:
    task = get_task(id)

Testing MCP Integration

Local Testing

  1. Configure MCP server in .mcp.json
  2. Install plugin locally (.claude-plugin/)
  3. Run /mcp to verify server appears
  4. Test tool calls in commands
  5. Check claude --debug logs for connection issues

Validation Checklist

  • MCP configuration is valid JSON
  • Server URL is correct and accessible
  • Required environment variables documented
  • Tools appear in /mcp output
  • Authentication works (OAuth or tokens)
  • Tool calls succeed from commands
  • Error cases handled gracefully

Debugging

Enable Debug Logging

bash
claude --debug

Look for:

  • MCP server connection attempts
  • Tool discovery logs
  • Authentication flows
  • Tool call errors

Common Issues

Server not connecting:

  • Check URL is correct
  • Verify server is running (stdio)
  • Check network connectivity
  • Review authentication configuration

Tools not available:

  • Verify server connected successfully
  • Check tool names match exactly
  • Run /mcp to see available tools
  • Restart Claude Code after config changes

Authentication failing:

  • Clear cached auth tokens
  • Re-authenticate
  • Check token scopes and permissions
  • Verify environment variables set

Quick Reference

MCP Server Types

TypeTransportBest ForAuth
stdioProcessLocal tools, custom serversEnv vars
SSEHTTPHosted services, cloud APIsOAuth
HTTPRESTAPI backends, token authTokens
wsWebSocketReal-time, streamingTokens

Configuration Checklist

  • Server type specified (stdio/SSE/HTTP/ws)
  • Type-specific fields complete (command or url)
  • Authentication configured
  • Environment variables documented
  • HTTPS/WSS used (not HTTP/WS)
  • ${CLAUDE_PLUGIN_ROOT} used for paths

Best Practices

DO:

  • ✅ Use ${CLAUDE_PLUGIN_ROOT} for portable paths
  • ✅ Document required environment variables
  • ✅ Use secure connections (HTTPS/WSS)
  • ✅ Pre-allow specific MCP tools in commands
  • ✅ Test MCP integration before publishing
  • ✅ Handle connection and tool errors gracefully

DON'T:

  • ❌ Hardcode absolute paths
  • ❌ Commit credentials to git
  • ❌ Use HTTP instead of HTTPS
  • ❌ Pre-allow all tools with wildcards
  • ❌ Skip error handling
  • ❌ Forget to document setup

Additional Resources

Reference Files

For detailed information, consult:

  • references/server-types.md - Deep dive on each server type
  • references/authentication.md - Authentication patterns and OAuth
  • references/tool-usage.md - Using MCP tools in commands and agents

Example Configurations

Working examples in examples/:

  • stdio-server.json - Local stdio MCP server
  • sse-server.json - Hosted SSE server with OAuth
  • http-server.json - REST API with token auth

External Resources

Implementation Workflow

To add MCP integration to a plugin:

  1. Choose MCP server type (stdio, SSE, HTTP, ws)
  2. Create .mcp.json at plugin root with configuration
  3. Use ${CLAUDE_PLUGIN_ROOT} for all file references
  4. Document required environment variables in README
  5. Test locally with /mcp command
  6. Pre-allow MCP tools in relevant commands
  7. Handle authentication (OAuth or tokens)
  8. Test error cases (connection failures, auth errors)
  9. Document MCP integration in plugin README

Focus on stdio for custom/local servers, SSE for hosted services with OAuth.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Mcp Integration AI skill do?

This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration.

Why use Mcp Integration on TypingMind?

Because you install it once and use it with any model. Mcp Integration is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Mcp Integration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anthropics/claude-plugins-official/tree/main/plugins/plugin-dev/skills/mcp-integration. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mcp Integration?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Mcp Integration?

As many as you like. As long as a model supports skills, you can use Mcp Integration with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mcp Integration AI skill free?

Yes. It is published on GitHub by anthropics under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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