mnemosyne-mcp 0.1.0

MCP server for Mnemosyne — semantic code retrieval with 6-signal hybrid search and AST-aware compression

mnemosyne-mcp

MCP server for Mnemosyne — a 6-signal hybrid code retrieval engine that reduces LLM context waste by 73%.

For the full reference, see MCP.md in the repository root.

Install

pip install mnemosyne-mcp

Register with Claude Code

claude mcp add mnemosyne -- mnemosyne-mcp

Or add to your project's .mcp.json:

{
  "mcpServers": {
    "mnemosyne": {
      "command": "mnemosyne-mcp",
      "args": []
    }
  }
}

Tools

mnemosyne.search

Search a codebase using 6-signal hybrid retrieval (BM25 + TF-IDF + symbol matching + usage frequency + predictive prefetch + optional dense embeddings) fused via Reciprocal Rank Fusion. Returns the most relevant code chunks within a configurable token budget, with AST-aware compression.

Parameters:

• query (string, required) — natural language or keyword query
• budget (integer, default 8000) — maximum token budget
• project_root (string, optional) — path to project root

mnemosyne.index

Index or re-index a codebase. Incremental by default (only processes changed files).

Parameters:

• project_root (string, optional) — path to project root
• full (boolean, default false) — force full re-index

mnemosyne.stats

Show index statistics: file count, chunk count, tokens, language breakdown, chunk types.

Parameters:

• project_root (string, optional) — path to project root

How it works

Mnemosyne indexes your codebase into local SQLite, scoring every chunk with six retrieval signals fused through Reciprocal Rank Fusion. AST-aware compression then strips boilerplate while preserving function signatures, control flow, and documentation — delivering exactly within your token budget.

Zero runtime dependencies beyond Python 3.11+. No API keys. No cloud services. Everything runs locally.

License

AGPL-3.0 — commercial licensing available from Cast Net Technology.