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Provides access to [Tesla](/mcp/servers/integrations/tesla) vehicle telemetry data including battery status, charging information, climate controls, heater settings, location/GPS data, and vehicle state through the Tessie API.

Tesla Tessie MCP Server

A Model Context Protocol (MCP) server that provides Tesla vehicle telemetry data via the Tessie API. Exposes vehicle status, battery, charging, climate, and location data as tools for LLM consumption.

Features

Intelligent Caching: Configurable data refresh intervals to minimize API calls
Thread-Safe: Concurrent access to cached data is safely handled
LLM-Optimized Output: Human-readable formatted strings for each data point
Comprehensive Telemetry: 30+ tools covering all vehicle data categories

Installation

# Clone the repository cd tessie_mcp # Create virtual environment python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate # Install dependencies pip install -r requirements.txt

Configuration

Environment Variables

Create a .env file in the project root:

# Required: Your Tessie API token TESSIE_TOKEN=your_tessie_api_token_here # Optional: Override vehicle plate (defaults to config.py) VEHICLE_PLATE=34MIE386 # Optional: Data refresh interval in minutes (default: 5) # Use 'realtime' to always fetch fresh data TELEMETRY_INTERVAL=5

Vehicle Configuration

The vehicle plate can also be configured in config.py:

PLATE = '34MIE386'

Usage

1. Create `.env` File

Copy the example and add your Tessie API token:

cp .env.example .env

Edit .env:

TESSIE_TOKEN=your_tessie_api_token_here VEHICLE_PLATE=34MIE386 TELEMETRY_INTERVAL=5

Get your token from: https://dash.tessie.com/settings/api

2. Running the MCP Server

Local Mode (STDIO)

source venv/bin/activate python -m src.server

Remote Mode (HTTP/SSE)

source venv/bin/activate python -m src.server --transport sse --port 8000

This starts an HTTP server with:

SSE endpoint: http://your-server:8000/sse
Health check: http://your-server:8000/health

3. Connecting to the MCP Server

Option A: Cursor IDE Integration

Add to your Cursor settings (~/.cursor/mcp.json or via Settings > MCP):

{ "mcpServers": { "tessie": { "command": "/path/to/tessie_mcp/venv/bin/python", "args": ["-m", "src.server"], "cwd": "/path/to/tessie_mcp" } } }

After adding, restart Cursor. The Tesla tools will appear in your tool list.

Option B: Claude Desktop Integration

Add to Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{ "mcpServers": { "tessie": { "command": "/path/to/tessie_mcp/venv/bin/python", "args": ["-m", "src.server"], "cwd": "/path/to/tessie_mcp" } } }

Option C: Direct Testing with MCP Inspector

# Install MCP inspector npx @anthropic-ai/mcp-inspector # In another terminal, run your server python -m src.server

Option D: Remote Connection (HTTP/SSE)

Start the server in SSE mode on your remote machine:

python -m src.server --transport sse --host 0.0.0.0 --port 8000

Then connect from a client using the SSE URL:

http://your-server-ip:8000/sse

For Cursor/Claude, configure with SSE transport:

{ "mcpServers": { "tessie-remote": { "transport": "sse", "url": "http://your-server-ip:8000/sse" } } }

Option E: Programmatic Usage (Python)

from src.telemetry import Telemetry # Create telemetry instance (reads from .env automatically) telemetry = Telemetry(plate="34MIE386", interval=5) # Get formatted data (for LLMs) print(telemetry.get_battery_level()) # "Battery is at 41%" print(telemetry.get_charging_state()) # "Vehicle is not connected to a charger" print(telemetry.get_location()) # "Vehicle is at 39.869430, 32.733333 facing N (2°)" # Get raw data (for programmatic use) print(telemetry._get_battery_level()) # 41 print(telemetry._get_energy_remaining()) # 27.76

Available Tools

Battery & Charging

Tool	Description
`get_battery_level`	Current battery percentage
`get_energy_remaining`	Remaining energy in kWh
`get_lifetime_energy_used`	Total lifetime energy consumption
`get_battery_heater_on`	Battery heater status (cold weather)
`get_charging_state`	Current charging status
`get_charge_limit_soc`	Charging limit percentage
`get_charge_port_door_open`	Charge port door status
`get_minutes_to_full_charge`	Time remaining to full charge
`get_charging_complete_at`	Estimated completion datetime
`get_battery_summary`	Comprehensive battery summary

Climate & Temperature

Tool	Description
`get_is_climate_on`	HVAC system status
`get_outside_temp`	Ambient temperature
`get_allow_cabin_overheat_protection`	COP enabled status
`get_supports_fan_only_cabin_overheat_protection`	Fan-only COP capability

Heaters

Tool	Description
`get_seat_heater_left`	Driver seat heater level
`get_seat_heater_right`	Passenger seat heater level
`get_seat_heater_rear_left`	Rear left seat heater level
`get_seat_heater_rear_center`	Rear center seat heater level
`get_seat_heater_rear_right`	Rear right seat heater level
`get_steering_wheel_heater`	Steering wheel heater status
`get_side_mirror_heaters`	Side mirror heaters status
`get_wiper_blade_heater`	Wiper blade heater status
`get_all_heater_status`	Summary of all heaters

Drive State & Location

Tool	Description
`get_location`	GPS coordinates and heading
`get_speed`	Current vehicle speed
`get_power`	Power usage/regeneration
`get_shift_state`	Current gear (P/R/N/D)
`get_active_route`	Active navigation info

Vehicle State

Tool	Description
`get_in_service`	Service mode status
`get_sentry_mode`	Sentry Mode status
`get_display_name`	Vehicle's custom name

Architecture

src/ ├── __init__.py # Package initialization ├── tessie_client.py # Tessie API client ├── telemetry.py # Telemetry class with caching └── server.py # MCP server entry point

Telemetry Class

The Telemetry class implements a dual-method pattern for each data field:

Private methods (_get_*): Return raw values for programmatic use
Public methods (get_*): Return formatted strings for LLM consumption

Example:

telemetry._get_battery_level() # Returns: 41 telemetry.get_battery_level() # Returns: "Battery is at 41%"

Caching Strategy

Data is cached with timestamps
On each request, elapsed time is checked against the interval
If stale, fresh data is fetched from Tessie API
Thread-safe access using locks

License

MIT

Tesla Tessie MCP Server

Tesla Tessie MCP Server

Features

Installation

Configuration

Environment Variables

Vehicle Configuration

Usage

1. Create `.env` File

2. Running the MCP Server

Local Mode (STDIO)

Remote Mode (HTTP/SSE)

3. Connecting to the MCP Server

Option A: Cursor IDE Integration

Option B: Claude Desktop Integration

Option C: Direct Testing with MCP Inspector

Option D: Remote Connection (HTTP/SSE)

Option E: Programmatic Usage (Python)

Available Tools

Battery & Charging

Climate & Temperature

Heaters

Drive State & Location

Vehicle State

Architecture

Telemetry Class

Caching Strategy

License

Resources

New MCP Servers

Latest Blog Posts

MCP directory API

Tesla Tessie MCP Server

Features

Installation

Configuration

Environment Variables

Vehicle Configuration

Usage

1. Create .env File

2. Running the MCP Server

Local Mode (STDIO)

Remote Mode (HTTP/SSE)

3. Connecting to the MCP Server

Option A: Cursor IDE Integration

Option B: Claude Desktop Integration

Option C: Direct Testing with MCP Inspector

Option D: Remote Connection (HTTP/SSE)

Option E: Programmatic Usage (Python)

Available Tools

Battery & Charging

Climate & Temperature

Heaters

Drive State & Location

Vehicle State

Architecture

Telemetry Class

Caching Strategy

License

Resources

New MCP Servers

Latest Blog Posts

MCP directory API

1. Create `.env` File