combine-memory-mcp

combine-memory-mcp

Persistent memory server for CMS Combine lessons, enabling saving and searching confirmed error-cause-fix chains across sessions and users.

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README

combine-memory-mcp

MCP server providing a persistent, shared memory of CMS Combine lessons for the combine-assistant stack. It complements the other two servers:

Piece Repo Role
Retrieval MCP combine-mcp Search/fetch over docs, paper, code, forum.
Execution MCP combine-run-mcp Run a Combine command in a sandbox.
Memory MCP this repo Remember confirmed lessons across sessions and users.

An entry is a short, distilled lesson — a confirmed error → cause → fix chain, or a non-obvious behavior verified against the docs/code/forum. It is not a session log: size caps at save time and a deliberately conservative save policy ("save less rather than too much", enforced via the server instructions) keep the store small and useful.

Tools

  • save_memory(title, lesson, namespace?, combine_version?, refs?, author?) — persist one lesson. Validation (size caps, namespace rules) happens server-side; rejected entries return {"error": ...}.
  • search_memory(query, namespace?, limit?) — BM25-ranked hits (id, title, score, snippet, …). Same ranking approach as combine-mcp, so scores read consistently across the stack.
  • fetch_memory(entry_id) — the full lesson for one hit.

Namespaces: shared (default — lessons useful to everyone) and user:<name> (personal context). Note: there is no authentication; namespaces are organizational, not access control. Nothing in this store is private — the server instructions forbid saving user analysis specifics.

Storage

SQLite (WAL mode), one table. The path comes from, in order: the --db flag, the COMBINE_MEMORY_DB env var, ./memory.db. The BM25 index is in-memory and rebuilds lazily whenever the store changes, so searches see saves immediately.

Running

pip install .

# local (stdio), DB in the current directory:
combine-memory-mcp serve

# remote (HTTP):
combine-memory-mcp serve --transport streamable-http --host 0.0.0.0 --port 8000 \
    --db /data/memory.db

Container / CERN PaaS

The Dockerfile builds a plain python:3.11-slim image (no Combine inside) that serves streamable-HTTP on port 8000 and expects the store at /data/memory.db. Deployment notes:

  • Attach a persistent volume (PVC) at /data — the pod filesystem is ephemeral; without the PVC the memory is wiped on every redeploy.
  • Run a single replica — SQLite has one writer; two pods sharing the file would corrupt it.
  • The image handles OpenShift's arbitrary-UID model (chgrp 0 / chmod g=u).

Tests

pip install -e ".[dev]" && pytest    # or: uv run pytest

License

MIT

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