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DimensionOff Grid AIAn offline AI suite that runs on your deviceHevy MCPManage your Hevy workout data from AI assistants via MCP.
FMRS25 / 100 · D77 / 100 · B
Reliability2 / 2012 / 20
Security and permissions7 / 2016 / 20
Maintenance10 / 2016 / 20
Documentation4 / 2018 / 20
Setup experience2 / 2015 / 20
Best for
  • Privacy-conscious users who want data to remain on-device
  • Users needing local AI capabilities on mobile or Mac
  • Users working with GGUF models or local-network model servers
  • Hevy PRO users who want AI assistants to directly access their workout data
  • People who prefer using MCP clients like Claude, Cursor, Codex for fitness tracking
  • Anyone needing summaries and insights from their training data
Not for
  • Users seeking a server with explicitly documented MCP tools and transport configuration
  • Users requiring cloud hosting, remote APIs, or verified MCP client compatibility
  • Devices without sufficient hardware resources for the selected models
  • Users without a Hevy PRO subscription (API key required)
  • Users who want to use the server without an API key
  • Those needing delete workflows (Hevy API does not expose delete endpoints)
Required permissions
  • Use device CPU, GPU, or NPU for local model inference
  • Access the microphone for on-device Whisper transcription
  • Access the camera for vision analysis
  • Access local files or documents for attachments and knowledge-base processing
  • Access the local network to connect to OpenAI-compatible remote LLM servers
  • Requires HEVY_API_KEY environment variable for Hevy API authentication
  • Can create, update, and replace workouts, routines, folders, templates, and body measurements via tools
  • Read operations can fetch workouts, routines, folders, templates, history, and user info
Risks and side effects
  • Model inference and image generation can consume substantial device resources and memory
  • Hexagon NPU support is marked experimental; some quantizations or model architectures may fall back to CPU or produce garbled output
  • When connected to a remote LLM server on the local network, data is sent to that service; the README does not specify its privacy policy
  • Tool calling may perform searches or query device information and the local knowledge base; no separate MCP permission boundary is documented
  • API key can be misused if leaked; do not expose in URLs, logs, or screenshots
  • Create operations may produce duplicates on retry; update operations replace existing records
  • The server sends data to the Hevy API and may send telemetry to external services unless disabled
Supported clientsClaude Desktop, Cursor, Codex, Antigravity
Tools026