Persistent AI Memory via Obsidian MCP: 16 Tools for Claude Cowork
A developer built a persistent memory system for Claude Cowork (Claude Opus 4.6) by connecting it to an Obsidian vault via a custom Model Context Protocol (MCP) server. The system solves session memory loss without bloating the context window.
Key Details
- Core architecture: An Obsidian vault acts as a queryable knowledge store outside the context window. The AI loads only a context manifest at session start, then queries specific knowledge on demand.
- Custom MCP server: A lightweight Python script exposing 16 tools that map to Obsidian's local REST API endpoints, with headers set explicitly. The server runs locally, allowing Claude to read, write, and search the vault.
- Structured vault: Uses frontmatter metadata and Dataview queries for structured retrieval.
- Context budget: Session start allows 5 MCP calls to keep context under control.
- Comparison to CLAUDE.md: The author notes that
CLAUDE.mdfiles solve project state (current state, next steps) but cannot scale to hold research, retrospectives, troubleshooting, or session history without overloading context.
Who It's For
Developers using Claude Cowork who need persistent memory across sessions for projects with extensive history, research, or troubleshooting logs.
📖 Read the full source: r/ClaudeAI
👀 See Also
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