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DimensionGBrainAn open-source brain layer for your AI agents, with synthesis, graph traversal, and gap analysis.BioMCPOne binary. One grammar. Evidence from the biomedical sources you already trust.
FMRS66 / 100 · C75 / 100 · B
Reliability8 / 2010 / 20
Security and permissions13 / 2016 / 20
Maintenance16 / 2018 / 20
Documentation16 / 2017 / 20
Setup experience13 / 2014 / 20
Best for
  • Personal knowledge management that requires actual answers beyond search (synthesis + gap analysis)
  • Teams wanting to build shared institutional memory (with OAuth scoping)
  • AI agents needing persistent memory (automatic ingestion, enrichment, consolidation)
  • Biomedical researchers
  • Clinicians
  • AI agents that need efficient access to biomedical literature and data analysis
Not for
  • Scenarios requiring real-time data streams (depends on scheduled syncs and crawling)
  • Users without API keys or willing to configure an embedding provider (requires at least one)
  • Users wanting a fully managed cloud service (requires self-hosting)
  • Users needing to write to upstream databases (read-only)
  • Users requiring direct access to closed datasets (e.g., COSMIC is not directly integrated)
  • Users expecting all advanced features without API keys
Required permissions
  • Read/write access to local filesystem (for brain repo and imports)
  • Network access to external APIs (unlocks embedding providers, LLMs, ingestion webhooks)
  • Environment variable access for API keys (e.g., OPENAI_API_KEY, etc.)
  • Local database (PGLite or Postgres)
  • Requires internet access to query public biomedical APIs
  • Optional API keys (NCBI, Semantic Scholar, OpenFDA, etc.) to improve rate limits or unlock features
  • Local read/write access for skills, cache, and local study data (e.g., `~/.local/share/biomcp`)
Risks and side effects
  • Package confusion: the 'gbrain' package on npm is unrelated and may cause conflicts; install only from GitHub
  • Data privacy: local data is secure, but remote deployments must secure OAuth tokens and API keys
  • LLM costs: 'think' and synthesis features consume LLM API calls, incurring expenses
  • Performance issues: large brain syncs may take time or stall (troubleshooting provided)
  • Upstream API rate limits may affect performance
  • Some data sources (e.g., KEGG) have licensing terms that restrict non-academic use
  • Features requiring API keys (e.g., OncoKB) may be incomplete without them
  • Local binary installations need regular updates for compatibility
Supported clientsClaude Desktop, Claude Code, Codex, Cursor, Windsurf, Perplexity, ChatGPT, Claude CoworkClaude Desktop, Claude Code, Codex, Other MCP stdio clients
Tools1011