EV Life Content MCP Server

EV Life Content MCP Server

Enables querying and retrieving content from electricvehicle.life, including search, section retrieval, full content, and summaries.

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Visit Server

README

EV Life Content MCP Server

This MCP (Model Context Protocol) server provides content querying tools for electricvehicle.life. It offers two deployment options: a local stdio-based server for direct Claude Desktop integration, and a Cloudflare Workers deployment for remote access.

Available Tools

The MCP server provides four content querying tools:

  1. search_content - Search for specific terms in electricvehicle.life content with context
  2. get_section - Retrieve specific sections by title/heading
  3. get_full_content - Get the complete content with optional truncation
  4. get_content_summary - Generate content statistics and table of contents

Quick Start

Option 1: Local Stdio Server (Recommended)

  1. Clone and install dependencies:
git clone <your-repo-url>
cd evlife-mcp-server
npm install
  1. Configure Claude Desktop by adding to your MCP config:
{
  "mcpServers": {
    "evlife-content": {
      "command": "node",
      "args": ["/path/to/evlife-mcp-server/mcp-stdio.js"],
      "env": {}
    }
  }
}
  1. Restart Claude Desktop and the tools will be available.

Option 2: Cloudflare Workers Deployment

  1. Prerequisites:

  2. Authenticate with Cloudflare:

npx wrangler login
  1. Deploy to Cloudflare Workers:
npm run deploy

This will deploy your MCP server to a URL like: evlife-mcp-server.<your-account>.workers.dev/sse

  1. One-Click Deploy (Alternative):

    Deploy to Workers

Cloudflare Workers Features

This MCP server leverages several Cloudflare Workers features:

  • Edge Computing: Runs close to users worldwide for low latency
  • Durable Objects: Maintains stateful MCP agent instances
  • Server-Sent Events: Real-time communication with MCP clients
  • No Cold Starts: Fast response times with Cloudflare's V8 isolates
  • Built-in Observability: Monitoring and analytics through Cloudflare dashboard

Worker Configuration

The server exposes two endpoints:

  • /sse - Server-Sent Events endpoint for MCP communication
  • /mcp - Standard MCP endpoint

Configuration is managed in wrangler.jsonc:

{
  "name": "evlife-mcp-server",
  "main": "src/index.ts",
  "compatibility_date": "2025-03-10",
  "durable_objects": {
    "bindings": [
      {
        "class_name": "MyMCP",
        "name": "MCP_OBJECT"
      }
    ]
  }
}

Development

Local Development with Wrangler

# Start the Cloudflare Workers dev server
npm run dev

# Run TypeScript type checking
npm run type-check

# Format code
npm run format

# Fix linting issues
npm run lint:fix

Local Development with Stdio Server

# Test the stdio server directly
node mcp-stdio.js

# The server will wait for MCP protocol messages on stdin

Project Structure

├── src/
│   └── index.ts           # Cloudflare Workers MCP server
├── mcp-stdio.js          # Local stdio MCP server
├── package.json          # Dependencies and scripts
├── wrangler.jsonc        # Cloudflare Workers config
├── CLAUDE.md            # Claude-specific documentation
└── README.md            # This file

Content Source

The server fetches content from https://electricvehicle.life/llms-full.txt and caches it for 5 minutes to improve performance. The content includes:

  • Personal blog posts and essays
  • Technical documentation
  • Project descriptions
  • Conference notes and insights

Test locally with MCP Inspector

npx @modelcontextprotocol/inspector

Connecting to Claude Desktop

For Local Stdio Server

Add this to your Claude Desktop MCP configuration:

{
  "mcpServers": {
    "evlife-content": {
      "command": "node",
      "args": ["/absolute/path/to/mcp-stdio.js"],
      "env": {}
    }
  }
}

For Deployed Workers (with mcp-remote)

{
  "mcpServers": {
    "evlife-content": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://your-worker-url.workers.dev/sse"
      ]
    }
  }
}

Connect to Cloudflare AI Playground

For deployed Workers, you can test the MCP server using Cloudflare AI Playground:

  1. Go to https://playground.ai.cloudflare.com/
  2. Enter your deployed MCP server URL (your-worker-url.workers.dev/sse)
  3. Test the content querying tools directly

Deployment Customization

Custom Domain (Optional)

To use a custom domain with your Cloudflare Worker:

  1. Add a custom domain in your Cloudflare dashboard
  2. Update wrangler.jsonc with your domain:
{
  "routes": [
    {
      "pattern": "mcp.yourdomain.com/*",
      "custom_domain": true
    }
  ]
}

Environment Variables

Add environment variables for configuration:

# Set environment variables
npx wrangler secret put API_KEY
npx wrangler secret put CONTENT_URL

Then access them in your Worker:

// In src/index.ts
const contentUrl = env.CONTENT_URL || "https://electricvehicle.life/llms-full.txt";

Troubleshooting

Common Issues

  1. MCP Connection Failed

    • Ensure the server URL is correct
    • Check that the Worker is deployed and accessible
    • Verify Claude Desktop configuration
  2. Content Fetching Errors

    • Check if https://electricvehicle.life/llms-full.txt is accessible
    • Verify network connectivity from the Worker
    • Monitor Cloudflare logs for fetch errors
  3. Development Server Issues

    • Run npm install to ensure dependencies are installed
    • Check Node.js version compatibility (v18+ recommended)
    • Use npm run type-check to identify TypeScript errors

Monitoring

  • View Worker logs in the Cloudflare dashboard
  • Use wrangler tail for real-time log monitoring
  • Monitor MCP server logs in Claude Desktop

Customization

To add your own tools:

  • Stdio server: Edit mcp-stdio.js and add new tool handlers
  • Workers server: Edit src/index.ts and add tools in the init() method

Example: Adding a New Tool

// In src/index.ts or mcp-stdio.js
this.server.tool(
    "new_tool",
    {
        parameter: z.string().describe("Tool parameter")
    },
    async ({ parameter }) => {
        // Tool implementation
        return {
            content: [{ type: "text", text: `Result: ${parameter}` }]
        };
    }
);

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