TeslaOnTarget

Bridge your Tesla vehicle with TAK (Team Awareness Kit) servers for real-time position tracking.

TeslaOnTarget connects your Tesla to a TAK server and streams live position and status as Cursor-on-Target (CoT) messages — for emergency response, fleet or personal tracking, or testing TAK systems with real vehicle data.

How it works

flowchart LR
    tesla["Tesla Owner API"]
    subgraph app["TeslaOnTarget container"]
        cli["cli<br/>per-vehicle threads"]
        api["tesla_api<br/>poll + dead reckoning"]
        mapper["vehicle_mapper<br/>payload to CoT dict"]
        cot["cot<br/>build CoT XML"]
        takc["tak_client<br/>TCP send"]
        health["health<br/>monitor + alerts"]
        cli --> api --> mapper --> cot --> takc
        health -.->|watches| takc
    end
    tesla -->|vehicle data every 10s| cli
    takc -->|CoT over TCP| takserver["TAK Server"]
    takserver --> clients["ATAK / iTAK / WebTAK"]
    health -.->|webhook/ntfy on stall| alert["Alert endpoint"]

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Poll Tesla → map the payload to a CoT event → send it to your TAK server, with 1 Hz dead-reckoning between polls and a health monitor that reconnects (and alerts) on failure. Full detail: docs/ARCHITECTURE.md.

Features

• Real-time tracking — GPS updates every 10s with 1Hz dead-reckoning in between
• Rich status — battery, charging, and parked-security (doors/windows/sentry) in the CoT remarks
• Multi-vehicle — track your whole account from one instance (iTAK / ATAK / WebTAK)
• Self-healing — health monitor reconnects on stalled sends and restarts for recovery
• Failure alerting — optional webhook/ntfy push when sends stall (opt-in)
• Battery-friendly — wakes the vehicle once, reports last position while it sleeps

Quick start (Docker)

docker pull ghcr.io/joshuafuller/teslaontarget:latest   # or :1.2.0 to pin a release

cp .env.example .env          # set TAK_SERVER and TESLA_USERNAME

# one-time Tesla login
docker run -it --env-file .env -v tesla_data:/data ghcr.io/joshuafuller/teslaontarget auth

# start tracking
docker run -d --env-file .env -v tesla_data:/data -v tesla_logs:/logs \
  --name teslaontarget --restart unless-stopped ghcr.io/joshuafuller/teslaontarget

Prefer a non-Docker install? uv sync, copy config.py.template → config.py, run uv run python -m teslaontarget.auth, then ./teslaontarget.sh start. Full guides below.

Requirements

• Python 3.11+ (bundled in the Docker image)
• A Tesla account with a vehicle
• A CoT-capable TAK server reachable over plaintext TCP

⚠️ Security

Only plaintext TCP to the TAK server is supported (no TLS yet). Keep TeslaOnTarget on the same LAN as your TAK server (ideally on the TAK host) or behind a VPN — do not expose it across the internet.

Configuration

Set via environment variables (Docker) or config.py (source). The essentials:

Setting	Description	Default
TAK_SERVER (+ TAK_PORT)	TAK server host/IP and port — Docker	required
COT_URL	Full tcp://host:port — source config.py	required
TESLA_USERNAME	Tesla account email	required
ALERT_WEBHOOK_URL	ntfy topic / webhook for failure alerts	(off)

Full reference (all options, multi-vehicle filtering, debug capture, what's transmitted): docs/CONFIGURATION.md.

Documentation

• Documentation index — start here
• Architecture · Docker guide · Tesla authentication · Configuration & operations · Troubleshooting
• CHANGELOG · Releases · Roadmap · Contributing

Known limitations

• No SSL/TLS — plaintext TCP only (planned; see the roadmap)
• Wakes the vehicle once on startup only (by design, to preserve battery)
• No authentication to the TAK server — relies on network security

License

MIT — see LICENSE. Not affiliated with Tesla, Inc. Use responsibly: mind Tesla API rate limits, battery consumption, and local laws on vehicle tracking.

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Made with ❤️ for the TAK community