Building an MCP Server for Tesla Before Elon Lost the Plot
summary
A working MCP server connects TeslaMate to LLMs so vehicle telemetry (drives, battery, GPS, tire pressure) becomes conversational: deployed on GCP with microservices in Kubernetes, Argo CD and Terraform, ingesting a ~15 GB proof‑of‑concept dataset, visualized in Graphana and streamed via MQTT; queries return concrete results (1,931 km work driving in 2025, ~5,000 km including trips) while battery decay forecasting runs, but security and context cost bite—tools are read‑only, auth via Entra ID auth, and adding one MCP server can consume ~40% of model context in practice with tradeoffs between cost and accuracy for Python Kubernetes Terraform.
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chapters (15)
- 0:00MCP in industrial settings
- 2:08AI explosion and LLM limits
- 6:04MCP vs RAG for context
- 10:00Democratizing systems with MCP
- 12:50Tesla cars for MCP demos
- 15:39Tesla MCP server architecture
- 18:49Visualizing Tesla data beyond Grafana
- 19:33MCP security and authentication
- 22:3024/7 MCP agent monitoring
- 26:24Tax deduction use case
- 30:15MCP security and governance
- 33:24Dangers of MCP democratization
- 36:34MCP context window limits
- 38:00MCP cost versus usage
- 39:29MCP future in industry
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