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DimensionLocal Deep Research (LDR) MCP ServerLocal-first deep research assistant exposing multi-engine search and cited reports to Claude over MCP.Hevy MCPManage your Hevy workout data from AI assistants via MCP.
FMRS70 / 100 · B77 / 100 · B
Reliability9 / 2012 / 20
Security and permissions14 / 2016 / 20
Maintenance18 / 2016 / 20
Documentation17 / 2018 / 20
Setup experience12 / 2015 / 20
Best for
  • Privacy-conscious researchers and developers who want to run LLMs and search fully locally
  • Users already running local models via Ollama, LM Studio, or llama.cpp
  • People who want to give Claude multi-engine academic search and structured report generation
  • Local, STDIO-based integration into Claude Desktop or Claude Code
  • 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
  • Multi-user or network-exposed deployments — this MCP server has no built-in authentication or rate limiting and is documented as local-use only
  • Users wanting a zero-config tool — it requires configuring an LLM provider and a search engine, and sometimes deploying SearXNG
  • Teams needing real-time multi-user collaboration features
  • 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
  • Access to a configured LLM (local endpoint or cloud API key)
  • Outbound network access to call configured search engines (arXiv, PubMed, SearXNG, Brave, etc.), unless restricted to local documents only
  • Local filesystem read access for analyze_documents to work with private documents
  • Read/write access to the local encrypted (SQLCipher) database
  • 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
  • The docs explicitly warn this MCP server is designed for local use only via STDIO transport, has no built-in authentication or rate limiting, and should not be exposed over a network without additional security controls
  • Credentials (e.g. API keys) are held in process memory during active sessions, a routine runtime risk the project mitigates with session-scoped credential lifetimes and core dump exclusion
  • Research queries are sent to whichever search engines are configured, and cloud LLM providers (OpenAI, Anthropic, Google, etc.) receive query/document content when selected
  • Docker's --network host mode can silently fail to expose ports or misroute localhost on Windows/WSL2/Mac
  • 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, Claude CodeClaude Desktop, Cursor, Codex, Antigravity
Tools826