Transport for London MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Transport for London as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Transport for London. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Transport for London?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Transport for London MCP Server
Connect to Transport for London (TfL) and access real-time London transit data through natural conversation — no API key needed.
LlamaIndex agents combine Transport for London tool responses with indexed documents for comprehensive, grounded answers. Connect 11 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Tube Status — Check real-time status of all Underground lines (Good Service, Minor/Severe Delays, Suspended)
- Line Details — Get detailed info about any tube, overground, DLR, Elizabeth line or tram route
- Bus Arrivals — Get live bus arrival predictions for any stop
- Journey Planning — Plan journeys between any two London locations with step-by-step directions
- Road Status — Check major road status and disruptions across London
- Bike Points — Find Santander Cycle docking stations with bike and dock availability
- Stop Search — Search for bus stops, tube stations and river piers by name
The Transport for London MCP Server exposes 11 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Transport for London to LlamaIndex via MCP
Follow these steps to integrate the Transport for London MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 11 tools from Transport for London
Why Use LlamaIndex with the Transport for London MCP Server
LlamaIndex provides unique advantages when paired with Transport for London through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Transport for London tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Transport for London tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Transport for London, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Transport for London tools were called, what data was returned, and how it influenced the final answer
Transport for London + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Transport for London MCP Server delivers measurable value.
Hybrid search: combine Transport for London real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Transport for London to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Transport for London for fresh data
Analytical workflows: chain Transport for London queries with LlamaIndex's data connectors to build multi-source analytical reports
Transport for London MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect Transport for London to LlamaIndex via MCP:
get_arrivals
Returns predicted arrival times, destination, line number, vehicle ID and expected time to station. Use the stop point ID (e.g. "490009056W") from search_stop. Get live arrival predictions for a bus stop
get_bike_point_detail
Get detailed info for a specific bike docking station
get_bike_points
Returns bike availability, dock availability, station locations and status. Useful for finding nearby bikes for cycling journeys. Search for Santander Cycle (Boris Bike) docking stations
get_journey
Returns multiple route options with estimated duration, walking distance, fare cost, number of changes and step-by-step directions. Input locations can be station names, addresses or postcodes. Plan a journey between two points in London
get_line_detail
Supports tube, overground, DLR, Elizabeth line, tram and river bus lines. Get detailed information about a specific TfL line
get_line_routes
Returns the ordered list of stations the line serves. Useful for understanding the full journey path of a tube line. Get the route sequence for a TfL line
get_line_status
Shows whether each line has Good Service, Minor Delays, Severe Delays, or is Suspended/Part Suspended. If no line IDs specified, returns all tube lines. Use line_ids to check specific lines (comma-separated, e.g. "central,victoria,northern"). Get real-time status for TfL tube lines
get_road_disruptions
Returns disruption details with severity, location, cause and estimated clearance times. Get current road disruptions in London
get_road_status
Shows whether roads have Good, Minor or Severe congestion. Get status of London major roads
get_stop_details
Useful for identifying the correct stop ID for arrival queries. Get details for a specific bus stop or station
search_stop
Returns matching stops with their IDs, locations, modes and routes. Use the returned IDs with get_arrivals or get_stop_details. Search for bus stops and stations by name
Example Prompts for Transport for London in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Transport for London immediately.
"What's the status of the Central line?"
"Plan a journey from King's Cross to Heathrow."
"When is the next bus at Oxford Circus?"
Troubleshooting Transport for London MCP Server with LlamaIndex
Common issues when connecting Transport for London to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTransport for London + LlamaIndex FAQ
Common questions about integrating Transport for London MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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Connect Transport for London to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.