Exposes a connected-vehicle OBD-II/telematics platform to AI agents, enabling vehicle health scoring, live data queries, DTC decoding, maintenance prediction, and gated remote commands via a pluggable data layer.
Enables LLMs to interact with vehicle CAN bus and OBD-II data through a simulated ECU environment. Provides tools for reading frames, decoding messages via DBC files, monitoring signals, and querying automotive diagnostics without requiring physical hardware.
An MCP server that exposes vehicle-diagnostic and CAN-bus domain logic as agent tools, with a LangGraph orchestration layer and a human-in-the-loop eval harness.
Enables LLMs to automatically diagnose coding errors through codebase search, test execution, and live debugger integration (DAP/V8 CDP). Provides a secure, policy-gated environment for investigating failures while preventing destructive operations.
Connects AI assistants to a local Codex engine for performing deep, project-level code reviews and automated refactoring. It enables context-aware bug fixes and multi-file analysis through a standardized bridge between modern AI clients and local development environments.
Enables LLM-driven agents to autonomously detect, diagnose, repair, verify, and prevent software and hardware failures on local and remote systems. Includes built-in safety checks and automatic rollbacks.