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Local semantic search for markdown notes — MCP server

Project description

mcp-recall-md

Local semantic search for your markdown notes — via MCP
Search by meaning, not keywords. 100% offline.

Install  ·   Tools  ·   Auto-indexing  ·   .recallignore  ·   Troubleshooting


Install

Option A: Python users

pip install mcp-recall-md

Add to your MCP config (.mcp.json for Claude Code, claude_desktop_config.json for Claude Desktop):

{
  "mcpServers": {
    "mcp-recall-md": {
      "command": "mcp-recall-md",
      "args": ["--vaults", "C:/Users/you/notes"]
    }
  }
}

Option B: Download exe (no Python needed)

  1. Download mcp-recall-md.exe from the latest release
  2. Put it in a permanent folder (e.g. C:\Tools\mcp-recall-md\)
  3. Add to MCP config:
{
  "mcpServers": {
    "mcp-recall-md": {
      "command": "C:/Tools/mcp-recall-md/mcp-recall-md.exe",
      "args": ["--vaults", "C:/Users/you/notes"]
    }
  }
}

Multiple vaults? Just list them:

"args": ["--vaults", "C:/notes/work", "C:/notes/personal", "C:/docs"]

Restart your app. Start asking:

"Search my knowledge base for Kubernetes networking"

"Find my notes about AWS Bedrock"


Tools

Tool Parameters What it does
index key, content Store or update an article
search query, limit Semantic similarity search
remove key Delete an article

Auto-indexing

When --vaults is provided, the server automatically:

  1. Indexes all existing .md files on startup
  2. Watches for new and modified files in real time

No separate watcher process needed — it's all one command.

Without --vaults, the server runs in manual mode (use the index tool to add content).


.recallignore

Drop a .recallignore file in any vault root to control which files get indexed. Uses standard .gitignore syntax.

Exclude specific folders:

.obsidian/
_templates/
drafts/

Include only specific folders (exclude everything else):

*
!notes/
!docs/

Each vault gets its own .recallignore — they're independent.


Troubleshooting

Problem Fix
Search returns nothing Make sure --vaults is set, or use the index tool manually
First run is slow Embedding model (~80 MB) downloads once
Need to debug Add --verbose flag

License

MIT

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