tfl-mcp-server

tfl-mcp-server

Provides real-time Transport for London data including line status, journey planning, and disruption information via the TfL Unified API.

Category
访问服务器

README

Transport for London MCP Server

⚠️ Important Disclaimer: This is not an official Transport for London (TfL) MCP server. This is an independent project that uses the publicly available TfL Unified API to provide transport data. It is not affiliated with, endorsed by, or officially supported by Transport for London.

A Model Context Protocol (MCP) server providing real-time Transport for London data, including line status, journey planning, and disruption information. This server is deployed on Cloudflare Workers and can be used with any MCP-compatible client like Claude Desktop.

Demo

With MCP-UI Support

Experience interactive visual cards and UI components with MCP-UI compatible clients (shown here using nanobot.ai):

Demo with MCP-UI

Without MCP-UI

For clients without MCP-UI support, the server returns JSON data:

Demo without MCP-UI

Features

This MCP server provides the following tools:

🎯 show_line_status_selector (NEW!)

Display an interactive selector with buttons for all TfL lines. This uses MCP-UI's externalUrl feature to load an interactive HTML interface in your MCP client.

  • Parameters: None
  • Output:
    • An interactive UI with clickable buttons for all available TfL lines (Victoria, Central, Northern, Piccadilly, Jubilee, Bakerloo, Circle, District, Hammersmith & City, Metropolitan, Waterloo & City, Elizabeth, DLR, Overground, and Tram)
    • Each button is styled with the official line color
    • Clicking a button automatically calls get_line_status for that line
    • Perfect for quickly checking status across multiple lines

Use Case Example: Ask "Show me the line status selector" or "Show status" to get an interactive view of all lines. Click any line button to instantly check its current status.

🚇 get_line_status

Get the current status of a specific TfL transport line with beautiful visual cards (MCP-UI support).

  • Parameters:
    • lineId: The line ID to query (e.g., 'central', 'piccadilly', 'northern', 'victoria')
  • Output: Returns both JSON data and a visual UI card with TfL branding, line colors, and status badges

MCP-UI Visual Responses

When used with MCP-UI compatible clients (like Claude Desktop with MCP-UI support), the server returns beautiful visual cards:

Good Service:

Victoria Line - Good Service

Severe Delays:

Central Line - Severe Delays

Minor Delays:

Northern Line - Minor Delays

The visual cards feature:

  • Official TfL roundel logo with dynamic line colors
  • Status badges (green for good service, red for severe delays, amber for minor delays)
  • Clean, professional design with TfL branding
  • Fully backward compatible - non-MCP-UI clients receive JSON data

🗺️ plan_journey

Plan journeys between two locations in London.

  • Parameters:
    • from: Starting location (postcode, address, or station name)
    • to: Destination location (postcode, address, or station name)
    • modes (optional): Transport modes to use (e.g., 'tube,bus,walking')
    • time (optional): Journey time in HH:MM format or 'now'
    • timeIs (optional): 'Departing' or 'Arriving'
    • date (optional): Journey date in YYYYMMDD format
    • walkingSpeed (optional): 'Slow', 'Average', or 'Fast'
    • cyclePreference (optional): Cycling preference options
    • optimize (optional): 'Time', 'LeastInterchange', or 'LeastWalking'
    • maxTransferMinutes (optional): Maximum transfer time in minutes
    • maxWalkingMinutes (optional): Maximum walking time in minutes

Getting Started

Try It Now (No Deployment Required)

Want to test the server before deploying your own? You can use the public demo instance!

For Claude Desktop:

  1. Open Claude Desktop Settings > Developer > Edit Config
  2. Add this configuration:
{
  "mcpServers": {
    "tfl": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://london-transport-mcp.anoopt.workers.dev/mcp"
      ]
    }
  }
}
  1. Restart Claude Desktop
  2. Start asking questions about London transport!

For VS Code (GitHub Copilot):

  1. Open VS Code Settings > Extensions > GitHub Copilot > MCP Servers
  2. Add this configuration:
{
  "servers": {
    "tfl": {
      "type": "http",
      "url": "https://london-transport-mcp.anoopt.workers.dev/mcp"
    }
  }
}
  1. Start the MCP server
  2. Start using TfL tools in Copilot Chat!

Quick Deploy

Deploy to Cloudflare Workers

Click the button above to deploy this MCP server to your Cloudflare Workers account with one click!

Manual Deployment

  1. Clone this repository
  2. Install dependencies:
    npm install
    
  3. Deploy to Cloudflare Workers:
    npm run deploy
    

Your MCP server will be deployed to a URL like: london-transport-mcp.<your-account>.workers.dev

Authentication (Optional)

This server supports optional TfL API key authentication. While the TfL API works without authentication, using an API key provides higher rate limits and better performance.

Without API Key: The server will work with TfL's public API limits (subject to rate limiting).

With API Key (Recommended):

  1. Get a free API key from TfL API Portal
  2. Pass the API key in the X-API-Key header when connecting to the server

Connect to Claude Desktop

To connect to your MCP server from Claude Desktop, update your Claude Desktop configuration:

  1. Go to Claude Desktop Settings > Developer > Edit Config
  2. Add one of the following configurations:

Using mcp-remote

With API Key:

{
  "mcpServers": {
    "tfl": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://london-transport-mcp.<your-account>.workers.dev/mcp",
        "--header",
        "X-API-Key: YOUR_TFL_API_KEY"
      ]
    }
  }
}

Without API Key:

{
  "mcpServers": {
    "tfl": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://london-transport-mcp.<your-account>.workers.dev/mcp"
      ]
    }
  }
}

Note: For local development, replace the URL with http://localhost:8787/mcp

Connect to Cloudflare AI Playground

You can also connect to your MCP server from the Cloudflare AI Playground:

  1. Go to https://playground.ai.cloudflare.com/
  2. Enter your deployed MCP server URL with the /mcp endpoint
  3. Add the X-API-Key header with your TfL API key
  4. Start using the TfL tools directly from the playground!

Local Development

For local development:

npm run dev

This will start the server locally at http://localhost:8787

API Key (Optional)

This server supports optional TfL API key authentication for higher rate limits. The API key is not required but recommended for production use.

To use without an API Key: Simply omit the X-API-Key header when connecting. The TfL API will apply standard rate limits.

To use with an API Key:

  1. Visit the TfL API Portal
  2. Register for a free account
  3. Create a new application to get your API key
  4. Pass the key in the X-API-Key header when connecting

Examples

Once connected, you can ask Claude things like:

  • "Show me the line status selector" or "Show status" - displays an interactive UI with all TfL lines
  • "Is the Northern line running ok?"
  • "What's the status of the Victoria line?"
  • "Plan a journey from King's Cross to Heathrow Airport"
  • "How do I get from Oxford Circus to Canary Wharf?"
  • "What's the fastest route from Wimbledon to Liverpool Street?"

Tech Stack

  • Runtime: Cloudflare Workers
  • Framework: Hono.js
  • MCP SDK: @modelcontextprotocol/sdk
  • Language: TypeScript
  • API: Transport for London Unified API

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is open source and available under the MIT License.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选