enquire-mcp
Enables AI agents to retain and intelligently query institutional knowledge across Obsidian vaults, reducing redundant context windows and improving decision…
Memory layer for AI agents over your Obsidian vault. Hybrid retrieval (BM25 + ML + BGE rerank, RRF-fused), HNSW + int8 quantization, agentic RAG (HyDE + sub-question), standalone Bases, PDFs+OCR. Open-source long-term memory for Claude Code/Desktop, Cursor, ChatGPT, Codex. MCP-native, MIT, SLSA-3.
- Ask Claude to search your Obsidian vault for architecture decisions related to a specific project
- Generate summaries of technical documentation by querying your knowledge base with follow-up questions
- Retrieve relevant code patterns and implementation examples from your personal notes during development
Enables AI agents to retain and intelligently query institutional knowledge across Obsidian vaults, reducing redundant context windows and improving decision quality in multi-turn engineering workflows.
Engineering teams using Claude Code or Cursor who need persistent, searchable memory across project documentation and technical notes.
https://github.com/oomkapwn/enquire-mcp
By oomkapwn
How to Get It
claude mcp add enquire-mcp -- npx -y enquire-mcp
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Search my Obsidian vault for architecture decisions related to a specific project
Trust Signals Auto-scanned
Data & Access
Community Pulse New
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 25 GitHub stars; 4 contributors; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 25 GitHub stars; 4 contributors; last commit 0d ago; license MIT.