MCP Servers

MCP Servers in Claude Code

Complete guide to Model Context Protocol server configuration and usage.

Overview

MCP (Model Context Protocol) allows Claude Code to connect to external servers that provide additional tools, resources, and capabilities. Supports 300+ external tools and services.

Transport Types

Adding MCP Servers via CLI

# HTTP server (recommended)
claude mcp add --transport http github https://api.githubcopilot.com/mcp/

# SSE server (deprecated)
claude mcp add --transport sse asana https://mcp.asana.com/sse

# Local stdio server
claude mcp add --transport stdio my-db -- npx -y @some/package

# With environment variables
claude mcp add --transport stdio -e AIRTABLE_API_KEY=YOUR_KEY airtable -- npx -y airtable-mcp-server

# With scope
claude mcp add --scope project server-name -- command args

# List configured servers
claude mcp list

# Get server details
claude mcp get server-name

# Remove server
claude mcp remove server-name

Installation Scopes

Configuration File

MCP servers are configured in .mcp.json at the project root.

Stdio Server

{
  "mcpServers": {
    "server-name": {
      "type": "stdio",
      "command": "executable",
      "args": ["arg1", "arg2"],
      "env": {
        "KEY": "value"
      },
      "disabled": false
    }
  }
}

HTTP Server

{
  "mcpServers": {
    "github": {
      "type": "http",
      "url": "https://api.githubcopilot.com/mcp/"
    }
  }
}

Environment Variable Expansion

{
  "mcpServers": {
    "my-server": {
      "command": "${CLAUDE_PLUGIN_ROOT}/servers/api",
      "args": ["--config", "${CLAUDE_PLUGIN_ROOT}/config.json"],
      "env": {
        "API_KEY": "${MY_API_KEY}",
        "PORT": "${PORT:-3000}"
      }
    }
  }
}

${VAR} expands to env var value. ${VAR:-default} provides fallback.

Configuration Locations

• Local: ~/.claude.json (personal, one project)
• Project: .mcp.json in project root (checked into git)
• User: ~/.claude.json with user scope (personal, all projects)

Fields

Adding MCP Servers via CLI

# Add server interactively
claude mcp add

# Add with name and command
claude mcp add server-name -- command arg1 arg2

# Add with scope
claude mcp add --scope project server-name -- npx -y @package/server

# Add with environment variables
claude mcp add server-name -e KEY=value -- command args

# List configured servers
claude mcp list

# Remove server
claude mcp remove server-name

# Get server details
claude mcp get server-name

Common MCP Servers

Filesystem Server

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/allowed/path"]
    }
  }
}

PostgreSQL Server

{
  "mcpServers": {
    "postgres": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-postgres"],
      "env": {
        "DATABASE_URL": "postgresql://user:pass@localhost:5432/dbname"
      }
    }
  }
}

GitHub Server

{
  "mcpServers": {
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_..."
      }
    }
  }
}

Brave Search

{
  "mcpServers": {
    "brave-search": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-brave-search"],
      "env": {
        "BRAVE_API_KEY": "BSA..."
      }
    }
  }
}

Puppeteer (Browser Automation)

{
  "mcpServers": {
    "puppeteer": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-puppeteer"]
    }
  }
}

Memory (Persistent Knowledge Graph)

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-memory"]
    }
  }
}

Slack

{
  "mcpServers": {
    "slack": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-slack"],
      "env": {
        "SLACK_BOT_TOKEN": "xoxb-...",
        "SLACK_TEAM_ID": "T..."
      }
    }
  }
}

Sentry

{
  "mcpServers": {
    "sentry": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-sentry"],
      "env": {
        "SENTRY_AUTH_TOKEN": "sntrys_..."
      }
    }
  }
}

Firecrawl (Web Scraping)

{
  "mcpServers": {
    "firecrawl": {
      "command": "npx",
      "args": ["-y", "firecrawl-mcp"],
      "env": {
        "FIRECRAWL_API_KEY": "fc-..."
      }
    }
  }
}

Context7 (Library Docs)

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@context7/mcp-server"]
    }
  }
}

Perplexity (AI Search)

{
  "mcpServers": {
    "perplexity": {
      "command": "npx",
      "args": ["-y", "perplexity-mcp"],
      "env": {
        "PERPLEXITY_API_KEY": "pplx-..."
      }
    }
  }
}

OAuth MCP Servers

Some MCP servers support OAuth authentication:

# Add OAuth-enabled server
claude mcp add --transport http \
  --callback-port 8080 \
  --client-id "my-client-id" \
  --client-secret "my-secret" \
  github https://api.githubcopilot.com/mcp/

OAuth Configuration

{
  "mcpServers": {
    "oauth-server": {
      "type": "http",
      "url": "https://api.example.com/mcp/",
      "oauth": {
        "clientId": "your-client-id",
        "clientSecret": "your-client-secret",
        "callbackPort": 8080,
        "scopes": ["read", "write"]
      }
    }
  }
}

Additional CLI Commands

# Add MCP server from JSON blob
claude mcp add-json my-server '{"command":"node","args":["server.js"]}'

# Import servers from Claude Desktop app
claude mcp add-from-claude-desktop

# Reset MCP server (clear cached state)
claude mcp reset server-name

Tool Naming Convention

MCP tools are exposed to Claude with the naming pattern:

mcp__<server-name>__<tool-name>

For example:

• mcp__filesystem__read_file
• mcp__postgres__query
• mcp__github__create_issue

SSE-Based Servers

For remote MCP servers using Server-Sent Events:

{
  "mcpServers": {
    "remote-server": {
      "url": "https://my-server.example.com/mcp/sse",
      "headers": {
        "Authorization": "Bearer token123"
      }
    }
  }
}

Building Custom MCP Servers

TypeScript Server (Recommended)

import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import {
  ListToolsRequestSchema,
  CallToolRequestSchema,
} from "@modelcontextprotocol/sdk/types.js";

const server = new Server(
  { name: "my-server", version: "1.0.0" },
  { capabilities: { tools: {} } }
);

// List available tools
server.setRequestHandler(ListToolsRequestSchema, async () => ({
  tools: [
    {
      name: "my_tool",
      description: "Does something useful",
      inputSchema: {
        type: "object",
        properties: {
          query: { type: "string", description: "The query" }
        },
        required: ["query"]
      }
    }
  ]
}));

// Handle tool calls
server.setRequestHandler(CallToolRequestSchema, async (request) => {
  if (request.params.name === "my_tool") {
    const { query } = request.params.arguments;
    return {
      content: [{ type: "text", text: `Result for: ${query}` }]
    };
  }
  throw new Error(`Unknown tool: ${request.params.name}`);
});

// Start server
const transport = new StdioServerTransport();
await server.connect(transport);

Python Server

from mcp.server import Server
from mcp.server.stdio import stdio_server
from mcp.types import Tool, TextContent

server = Server("my-server")

@server.list_tools()
async def list_tools():
    return [
        Tool(
            name="my_tool",
            description="Does something useful",
            inputSchema={
                "type": "object",
                "properties": {
                    "query": {"type": "string"}
                },
                "required": ["query"]
            }
        )
    ]

@server.call_tool()
async def call_tool(name: str, arguments: dict):
    if name == "my_tool":
        return [TextContent(type="text", text=f"Result: {arguments['query']}")]
    raise ValueError(f"Unknown tool: {name}")

async def main():
    async with stdio_server() as (read, write):
        await server.run(read, write)

import asyncio
asyncio.run(main())

Troubleshooting

Server Not Starting

# Check server status
claude mcp list

# Test server manually
echo '{"jsonrpc":"2.0","method":"initialize","params":{"capabilities":{}},"id":1}' | npx -y @package/server

# Check Claude Code logs
claude --verbose

Common Issues

1. Missing env vars — Ensure API keys are set in the env field
2. npx cache — Use npx -y to auto-accept package install
3. Path issues — Use absolute paths for command when needed
4. Permission denied — Ensure server executable has execute permission
5. Port conflicts — For SSE servers, check port availability

Security Considerations

• MCP servers run with full system access — vet servers carefully
• API keys in .mcp.json should be in .gitignore or use env var references
• Prefer official @modelcontextprotocol/server-* packages
• Review server source code before adding third-party servers
• Use project-scoped config over user-scoped for sensitive servers

MCP Prompts — The Most Overlooked Primitive

Most engineers only use MCP Tools and miss this entirely. MCP Prompts are the highest-leverage primitive in the MCP spec.

MCP has three primitives: Tools (Claude invokes), Resources (data sources), and Prompts (pre-built conversation starters). Prompts are server-defined templates that prime Claude with everything needed for complex workflows — available via slash commands in the UI or programmatic invocation.

What Prompts Can Do

A Prompt is a structured message template that a server exposes. When invoked, it injects a complete, expert-quality system message into the conversation. Unlike Tools (which Claude calls to get data), Prompts set up how Claude should think and act for the entire workflow.

Prompts vs Tools:

Implementing Prompts in a Custom Server

import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import {
  ListPromptsRequestSchema,
  GetPromptRequestSchema,
} from "@modelcontextprotocol/sdk/types.js";

const server = new Server(
  { name: "my-server", version: "1.0.0" },
  { capabilities: { prompts: {}, tools: {} } }  // declare prompts capability
);

// List available prompts
server.setRequestHandler(ListPromptsRequestSchema, async () => ({
  prompts: [
    {
      name: "deploy-checklist",
      description: "Run full pre-deployment verification checklist",
      arguments: [
        {
          name: "environment",
          description: "Target environment (staging/production)",
          required: true
        }
      ]
    },
    {
      name: "security-review",
      description: "Deep security audit of recent changes",
      arguments: []
    }
  ]
}));

// Return prompt messages when invoked
server.setRequestHandler(GetPromptRequestSchema, async (request) => {
  const { name, arguments: args } = request.params;

  if (name === "deploy-checklist") {
    const env = args?.environment ?? "staging";
    return {
      messages: [
        {
          role: "user",
          content: {
            type: "text",
            text: `You are a deployment safety engineer. Run a complete pre-deployment checklist for the ${env} environment:
1. Check all tests pass
2. Verify no .env files are staged
3. Confirm version bump in package.json
4. Review last 3 commits for accidental secrets
5. Check docker image tags are not :latest
6. Verify rollback plan is documented

Report each item as PASS/FAIL/WARN with a one-line reason.`
          }
        }
      ]
    };
  }

  if (name === "security-review") {
    return {
      messages: [
        {
          role: "user",
          content: {
            type: "text",
            text: `You are a security engineer. Review the recent git diff for:
- Hardcoded credentials or API keys
- SQL injection vulnerabilities
- XSS attack surfaces
- Insecure deserialization
- Path traversal vulnerabilities
- Missing auth checks on new endpoints

Run git diff HEAD~3 and analyze every changed file.`
          }
        }
      ]
    };
  }

  throw new Error(`Unknown prompt: ${name}`);
});

Why Prompts Beat Mega-CLAUDE.md

Instead of loading 500 lines of deployment instructions into every session, expose a deploy-checklist prompt. It loads zero tokens at session start and activates only when needed.

Pattern: One Prompt = one expert persona + one workflow. Keep Prompts focused.

Real-World Prompt Ideas

Cost Impact

Prompts inject messages only when invoked. A Prompt with 500 tokens of expert instructions costs nothing until used, vs CLAUDE.md where those tokens load every session.

Rough math: 10 Prompts × 500 tokens each = 5,000 tokens available on demand vs 5,000 tokens consumed per session if put in CLAUDE.md.