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Vinkius runs on Windsurf

How to Use the TfL MCP in Windsurf

Build smart, multi-step workflows with Windsurf and the TfL MCP Server.

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Works with every AI agent you already use

…and any MCP-compatible client

TfL MCP on Cursor AI Code Editor MCP Client TfL MCP on Claude Desktop App MCP Integration TfL MCP on OpenAI Agents SDK MCP Compatible TfL MCP on Visual Studio Code MCP Extension Client TfL MCP on GitHub Copilot AI Agent MCP Integration TfL MCP on Google Gemini AI MCP Integration TfL MCP on Lovable AI Development MCP Client TfL MCP on Mistral AI Agents MCP Compatible TfL MCP on Amazon AWS Bedrock MCP Support
MCP Servers — Included with Plan
Vinkius runs on Windsurf

Connect TfL MCP to Windsurf

Create your Vinkius account to connect TfL to Windsurf — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Key Capabilities

Plan complex trips across London.

The `get_journey` tool plans a trip between two locations using all major TfL transport modes. It gives you full route options, showing total duration, CO2 savings, and how many transfers are involved. You tell your agent where you're going—say, from Paddington to Greenwich—and it figures out the best way to get there, providing detailed leg-by-leg instructions for tube, bus, walking, or cycling.

Check real-time arrivals at any stop.

Need to know when the next train is coming? The `get_arrivals` tool predicts arrival times for specific TfL stops. You just feed it a station ID and tell your agent what you're looking for, like 'Northern Line trains at Bank.' It returns predicted arrival times in minutes and exact timestamps, letting you coordinate transfers across the entire London network without guesswork.

Discover all stops and stations.

Don't know where to start your search? The `search_stop_point` tool finds matching TfL stop points by name or location. It gives you IDs, common names, what transport modes serve the spot, and its coordinates. This is perfect for when you need to find a station near an address, like 'find the tube station near Covent Garden,' so your agent can gather all the necessary details before running a plan.

Setup guide

Set up TfL MCP in Windsurf

Prerequisites

  • Windsurf IDE installed (macOS, Windows, or Linux)
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Open MCP configuration

    Click the Cascade assistant icon in the sidebar, then click the hammer icon (🔨) at the top of the panel. Select "Configure" to open ~/.codeium/windsurf/mcp_config.json.

  2. 2

    Add the TfL MCP

    Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.

  3. 3

    Refresh MCPs

    Go back to the hammer icon (🔨) in Cascade and click "Refresh". Windsurf will detect the new server. No full restart is needed — the connection is hot-reloaded.

  4. 4

    Verify in Cascade

    Start a new Cascade conversation and ask something like "Show my TfL payment history." If connected, Cascade will call the TfL tools directly. You will see a green dot next to the server name in the MCP panel.

mcp_config.json
{
  "mcpServers": {
    "tfl-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by TfL. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about TfL MCP in Windsurf

Windsurf handles multi-step processes. You set a goal, and your agent calls `get_journey`, which compares all available modes—tube, bus, rail, walking—to give you the best path from start to finish.
You use `get_bike_points` or `get_place_search`. The agent lists all Santander Cycles docking stations across London and tells you the current number of available bikes and empty docks at any specific spot.
The `get_line_status` tool checks overall reliability. You ask about the Victoria Line, and it immediately tells you if there are Minor Delays or if service is Good Service. It’s crucial before starting any trip.
Absolutely. The `get_road_disruptions` tool checks for roadworks or incidents affecting specific roads, like the A4. This helps your agent adjust plans if driving is suddenly out of options.
This server handles geographic coordinates and general stop point metadata (IDs, names). It doesn't access personal trip history or private user accounts. The data is limited to public transport status.

Start using the TfL MCP today

We host it, we monitor it, we maintain it. You just paste one token.

Built & Managed by Vinkius 30s setup 12 tools

We've already built the connector for TfL. Just plug in your AI agents and start using Vinkius.

No hosting. No infrastructure. No complex setup.
All 12 tools are live and waiting. You're up and running in seconds.

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