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DimensionAsk Ollama MCP ServerBridge Claude with local Ollama models for private AI-to-AI collaboration — no API keys, fully local.Context7Upstash's official server providing up-to-date third-party library docs for AI coding assistants
FMRS54 / 100 · D80 / 100 · B
Reliability8 / 2014 / 20
Security and permissions11 / 2016 / 20
Maintenance12 / 2017 / 20
Documentation12 / 2015 / 20
Setup experience11 / 2018 / 20
Best for
  • Teams or individuals with strict data-privacy requirements whose code cannot leave the machine
  • Developers already running Ollama locally who want to reuse that compute
  • Claude Code, Cursor, or Codex CLI users who want a second opinion from a different model
  • Users who want to avoid per-token API costs
  • Developers using fast-moving frameworks/libraries worried about the AI suggesting stale code
  • Scenarios wanting zero-config documentation lookup
Not for
  • Environments without Ollama installed or running
  • Workflows needing large cloud-model capability or very large-context reads
  • Users wanting multi-provider parallel fan-out (multi-llm) or cross-provider orchestration — use the unified @ask-llm/mcp instead
  • Users seeking official vendor support or an official relationship
  • Looking up internal/private codebase documentation (Context7 targets publicly published open-source libraries)
  • Cases needing very high coverage of obscure, niche libraries (coverage depends on what Context7's platform has indexed)
Required permissions
  • Local process communication with the MCP client over stdio
  • Access to the local Ollama HTTP service (default http://localhost:11434, configured via OLLAMA_HOST)
  • Reads prompt content passed by the MCP client (the code or text sent to local Ollama)
  • Usable without an API key (subject to a free-tier rate limit); CONTEXT7_API_KEY is an optional credential for higher quota
  • Read-only documentation lookup — no code execution or local filesystem access involved
Risks and side effects
  • Prompt content is sent to the local Ollama service; if OLLAMA_HOST is misconfigured to a remote host, data could leave the machine
  • Local models are generally weaker than frontier cloud models, so reviews may be incomplete or produce false positives
  • If the requested model has not been pulled locally, the call fails with an ollama pull error
  • Third-party, unofficial project — not endorsed by Anthropic, Google, OpenAI, or xAI
  • Long local inference may exceed the default 5-minute timeout (GMCPT_TIMEOUT_MS) and be interrupted
  • The free tier has limited quota — high-frequency use may hit rate limits
  • Documentation content comes from Context7's platform index, so its accuracy and freshness depend on that platform's crawl cadence
Supported clientsClaude Desktop, Claude Code, Cursor, CodexClaude Code, VS Code, Cursor, Cline, Amp
Tools32