by cobanov
A Model Context Protocol (MCP) server that provides access to your TeslaMate database, allowing AI assistants to query Tesla vehicle data and analytics.
# Add to your Claude Code skills
git clone https://github.com/cobanov/teslamate-mcpGuides for using ai agents skills like teslamate-mcp.
Last scanned: 5/30/2026
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}teslamate-mcp is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by cobanov. A Model Context Protocol (MCP) server that provides access to your TeslaMate database, allowing AI assistants to query Tesla vehicle data and analytics. It has 135 GitHub stars.
Yes. teslamate-mcp passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/cobanov/teslamate-mcp" and add it to your Claude Code skills directory (see the Installation section above).
teslamate-mcp is primarily written in Python. It is open-source under cobanov on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh teslamate-mcp against similar tools.
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TeslaMate records everything your car does into PostgreSQL, and its Grafana dashboards answer the questions someone anticipated. The interesting ones usually arrive later — is the battery actually degrading or was it just cold?, what did charging cost me at home versus on the road?, which drive was that weirdly inefficient one?
This is a Model Context Protocol server that hands that database to an AI client, so those questions get answered without you writing SQL.
You ▸ has my battery actually degraded this year?
⚙ get_battery_capacity_trend(days=365)
Usable capacity, estimated from your charging sessions rather
than rated range:
2025-11 53.8 kWh
2026-02 53.1 kWh
2026-07 52.4 kWh
About 2.6% over eight months, which is unremarkable. The
February dip tracks outside temperature, not capacity —
get_average_efficiency_by_temperature shows the same shape.
run_sql for anything they don't cover, live schema introspection, and 3 interactive chart tools.car_name, days, limit, and threshold arguments. Call one with no arguments and you get the full classic report.show_charging_curve, show_battery_degradation, and show_drive_route render self-contained SVG. Everywhere else they return the same rows.run_sql executes in a READ ONLY transaction that is always rolled back. The single write tool is off by default and can only touch one column.Requires a running TeslaMate with PostgreSQL, and Python 3.11+ (or just Docker).
git clone https://github.com/cobanov/teslamate-mcp.git
cd teslamate-mcp
cp env.example .env # set DATABASE_URL
uv sync
Point your client at it — for Claude Desktop or Cursor:
{
"mcpServers": {
"teslamate": {
"command": "uv",
"args": ["--directory", "/path/to/teslamate-mcp", "run", "teslamate-mcp", "stdio"]
}
}
}
Ask it something. teslamate-mcp list-tools prints everything it found.
docker run -d -p 8888:8888 \
-e DATABASE_URL='postgresql://teslamate:…@host:5433/teslamate' \
-e AUTH_TOKEN="$(uv run teslamate-mcp gen-token | cut -d= -f2)" \
ghcr.io/cobanov/teslamate-mcp:latest
The endpoint is /mcp, the probe is /health. Multi-arch images (amd64, arm64) ship with every release.
This database is your location history. Keep it on a private network — a VPN or Tailscale — rather than the open internet. Deployment covers the options.
Everything beyond this page lives in the wiki:
| Tool Reference | All 35 tools, their parameters, what each returns |
| Configuration | Every environment variable, with guidance |
| Deployment | Docker, images, proxies, exposure, troubleshooting |
| Writing Queries | Add your own tool with a .sql + .toml pair — no Python |
| Write Tools | The opt-in charging-cost write path and its grant |
| Development | Setup, tests, layout, releasing |
Issues and pull requests are welcome — see CONTRIBUTING.md. Adding a query needs no Python at all: drop a .sql file and a .toml sidecar into src/teslamate_mcp/queries/ and the registry picks it up.
A large part of the 0.9 feature line — typed parameters, twelve new queries, MCP Apps, and the SDK v2 migration — was contributed by @batubozkan.
MIT — see LICENSE.