TeslaMate
This MCP server provides comprehensive access to TeslaMate database analytics, enabling AI assistants to query Tesla vehicle data including battery health, charging patterns, driving efficiency, location analytics, and software update history. Built by Mert Cobanov using Python with FastMCP and psycopg, it offers 20 pre-built analytical tools covering everything from basic car information to unusual power consumption detection, plus custom SQL query capabilities with safety validation that only allows SELECT statements. The implementation supports both local stdio and remote HTTP deployment with optional bearer token authentication, making it valuable for Tesla owners who want to analyze their vehicle data through natural language queries, track battery degradation over time, optimize charging habits, or build custom dashboards and reports from their TeslaMate installation.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/cobanov/teslamate-mcp
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve TeslaMate from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.