Tesla MCP Server

Tesla MCP Server

An MCP server that connects to the Tesla Fleet API, allowing users to control vehicles and retrieve real-time status updates through Claude and other AI assistants. It supports functions such as waking up vehicles, viewing detailed vehicle information, and debugging via both stdio and HTTP/SSE transports.

Category
Visit Server

README

Tesla MCP Server

A Model Context Protocol (MCP) server for the Tesla Fleet API. Control your Tesla and get vehicle data (location, wake up, list cars) from any MCP-capable AI assistant or agent.

Features

  • list_cars — List your vehicles and get IDs for use with other tools
  • get_vehicle_location — Current GPS location and Google Maps link (parking monitor style)
  • wake_up — Wake a vehicle from sleep
  • refresh_vehicles / debug_vehicles — Refresh list and debug info
  • HTTP/SSE mode — Host as a web service; each user brings their own Tesla Developer credentials (no server-side secrets required)

Security

  • We never see or store your Tesla password. Sign-in is via Tesla’s OAuth in your browser.
  • HTTP mode: Credentials and tokens are stored in memory per session only; not written to disk.
  • No sensitive data in logs — We do not log tokens, full session IDs, or API response bodies.
  • Before you commit: Run ./check-secrets.sh to catch accidental hardcoded secrets.

See SECURITY.md for details and how to report issues.


Quick Start (Hosted — recommended)

Use the server without running anything locally. Each user connects with their own Tesla account.

1. Add the server in your MCP client

  • Server URL: https://tesla-mcp.onrender.com/sse
    (Or use your own deployed URL; see Deploy below.)

2. First time: connect your Tesla

  1. Use a tool (e.g. get_setup_url) — the agent will return a link.
  2. Open the link and enter your Tesla Developer Client ID and Client Secret.
  3. Log in with your Tesla account when redirected.
  4. On the success page, copy the connection URL (e.g. https://.../sse?token=...). Use that URL as your MCP server URL in your client so reconnects keep you logged in. Keep it private.
  5. If you don’t add that URL, your client may get a new session on each reconnect and ask you to set up again.

Getting Tesla Developer credentials: Create an app at developer.tesla.com. Set the redirect URI to https://YOUR_SERVER_URL/auth/callback (e.g. https://tesla-mcp.onrender.com/auth/callback).

Render: Set Instance count to 1 (Dashboard → your service → Settings) so all requests hit the same server and your session isn’t lost.


Quick Start (Local)

Option A: HTTP server (multi-user, browser auth)

git clone https://github.com/Sara3/Tesla-MCP.git
cd Tesla-MCP
npm install
npm run build
npm run start:http
  • Open http://localhost:3000 and follow the setup link to add your Tesla Developer credentials and sign in.
  • In your MCP client, use Server URL: http://localhost:3000/sse (for production use HTTPS and set BASE_URL).

Option B: Stdio (single user, .env only)

For a single user with credentials in .env:

# .env
TESLA_CLIENT_ID=...
TESLA_CLIENT_SECRET=...
TESLA_REFRESH_TOKEN=...
npm run build
npm start

Configure your MCP client to run the server command (e.g. node run-mcp.js). Get a refresh token with npm run get-token.


Environment variables

Variable Required Description
HTTP mode
BASE_URL Yes (production) Public HTTPS URL of your server (e.g. https://tesla-mcp.onrender.com)
TESLA_CLIENT_ID Optional If set with TESLA_CLIENT_SECRET, users go straight to the Tesla login page (no setup page)
TESLA_CLIENT_SECRET Optional Server Tesla app secret; use with TESLA_CLIENT_ID
PORT No Port (default 3000)
HOST No Bind address (default 0.0.0.0)
Stdio mode
TESLA_CLIENT_ID Yes From developer.tesla.com
TESLA_CLIENT_SECRET Yes From developer portal
TESLA_REFRESH_TOKEN Yes From npm run get-token

Never commit .env or keys/. Run ./check-secrets.sh before pushing.


Tools (MCP)

Tool Description
get_setup_url Get the URL to set up Tesla Developer credentials
get_auth_url Get the URL to connect your Tesla account (after setup)
list_vehicles List vehicles and their IDs (use with other tools)
get_vehicle_location Current location (lat/long + Google Maps link); takes vehicle_id
wake_up Wake a vehicle; takes vehicle_id
refresh_vehicles Refresh the vehicle list from the API
debug_vehicles Debug info (ids, vins, state)

For vehicle_id you can use id, vehicle_id, or vin from list_cars.


Deploy

Render

  1. Connect your GitHub repo at render.com → New → Web Service.
  2. Build command: npm install && npm run build
    Start command: npm run start:http
  3. Add env var: BASE_URL = https://YOUR-SERVICE.onrender.com
  4. Users set their Tesla app redirect URI to https://YOUR-SERVICE.onrender.com/auth/callback.

Docker

docker build -t tesla-mcp .
docker run -p 3000:3000 -e BASE_URL=https://your-domain.com tesla-mcp

Production: Use HTTPS and set BASE_URL to your public URL. On Render, set Instance count to 1 so sessions persist. See SECURITY.md.


Troubleshooting

Session keeps resetting / setup keeps asking

  1. Confirm credentials were saved — After submitting the setup form, you should see a green "Credentials saved successfully" message. If you see that, your Client ID and Secret were saved for that session.
  2. If setup keeps appearing, double-check in your Tesla Developer App:
    • Client ID and Client Secret are correct (copy from the app page).
    • Redirect URI is set exactly to your server’s callback URL, for example:
      • Render: https://tesla-mcp.onrender.com/auth/callback
      • Local: http://localhost:3000/auth/callback Any typo or extra slash will cause Tesla to reject the auth and the session will not persist.

“Authenticating your account” spinner never stops

Tesla should redirect you back to this app; if the spinner never finishes, the redirect may be failing. Check that your Tesla app’s Redirect URI is exactly https://tesla-mcp.onrender.com/auth/callback (or your BASE_URL + /auth/callback). Try in a normal browser window with extensions disabled so nothing blocks the redirect.

Session “doesn’t save” in incognito / have to log in again

Sessions are stored on the server, not in the browser. Incognito doesn’t keep cookies, but we don’t use cookies for your session—we use the connection URL with the token. After you log in, you must copy the connection URL (e.g. https://.../sse?token=...) from the success page and use that URL as your MCP server URL. If you use the plain /sse URL without the token, each new connection gets a new session and you’ll be asked to set up or log in again.

Tesla login page shows errors or won’t load (CSP, “inline script”, fingerprint, etc.)

Those errors come from Tesla’s login site (auth.tesla.com), not from this server. Browsers or extensions (e.g. ad blockers, Cursor, or other injectors) can block scripts on Tesla’s page and break login.

  • Try in a private/incognito window with extensions disabled.
  • Try another browser or a clean profile without extensions.
  • Temporarily allow auth.tesla.com in your ad/tracking blocker so Tesla’s scripts (and reCAPTCHA) can load.

Scripts

Command Description
npm run build Build TypeScript
npm run start Run stdio MCP server
npm run start:http Run HTTP/SSE server
npm run dev:http Run HTTP server (dev, with ts-node)
npm run get-token Get Tesla refresh token (local browser flow)
npm run test-api Test Tesla API connection
npm run register Register app with Tesla (uses ngrok)
./check-secrets.sh Check for accidental secrets in code

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured