combine-memory-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@combine-memory-mcpsearch memory for 'invalid value for systematic' fix"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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 | Search/fetch over docs, paper, code, forum. | |
Execution 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.
Related MCP server: Mind Keg MCP
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.dbContainer / 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 pytestLicense
This server cannot be installed
Maintenance
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