How do I use IMS MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@IMS MCP Server search my memories for the project requirements we discussed last session" 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.

IMS MCP Server

MCP server that exposes the Integrated Memory System (IMS) as tools via the Model Context Protocol Python SDK.

It wraps the existing IMS HTTP backend (session-memory, memory-core, context-rag) and makes those capabilities available to MCP-aware clients (e.g. mcphub, Warp, VS Code, LibreChat).

Prerequisites

Python 3.10+
An IMS backend running somewhere reachable (FastAPI/Uvicorn service), e.g.:
- http://localhost:8000, or
- http://ims.delongpa.com
The integrated-memory-system repo checked out on disk in this layout (relative to this project):

<some-parent-dir>/ skills/ integrated-memory-system/ # IMS FastAPI project (provides IMSClient) ims-mcp/ # this repo

server.py imports IMSClient from skills/integrated-memory-system/app/ims_client.py using a relative path; if your layout is different, adjust server.py accordingly.

Installation (venv + pip)

From the ims-mcp directory:

python3 -m venv .venv . .venv/bin/activate pip install -r requirements.txt

This installs the official MCP Python SDK (mcp[cli]).

Configuration

The MCP server talks to IMS via environment variables:

IMS_BASE_URL (required)
- Base URL of the IMS HTTP service, e.g. http://localhost:8000 or https://ims.delongpa.com.
IMS_HTTP_TIMEOUT (optional, default 5.0 seconds)
IMS_CLIENT_NAME (optional, default "ims-mcp")

Example:

export IMS_BASE_URL="http://ims.delongpa.com" export IMS_HTTP_TIMEOUT="5.0" export IMS_CLIENT_NAME="ims-mcp"

Running the MCP server locally

With the venv activated and IMS_BASE_URL set:

. .venv/bin/activate export IMS_BASE_URL="http://localhost:8000" # or your IMS URL python server.py

The server runs over stdio, which is what MCP clients expect when they spawn it as a subprocess.

mcphub configuration example

To use this server from mcphub on a host where you cloned this repo to /opt/mcps/ims-mcp and created the venv as above, add an entry like:

"IMS-MCP": { "type": "stdio", "command": "/opt/mcps/ims-mcp/.venv/bin/python", "args": [ "/opt/mcps/ims-mcp/server.py" ], "env": { "IMS_BASE_URL": "http://ims.delongpa.com" } }

Adjust paths and IMS_BASE_URL to match your environment.

Exposed tools

The MCP server exposes the following tools (namespaces follow the IMS service names):

ims.context-rag.context_search
- Wrapper over POST /context/search.
ims.memory-core.store_memory
- Wrapper over POST /memories/store.
ims.memory-core.find_memories
- Wrapper over POST /memories/search.
ims.session-memory.auto_session
- Wrapper over POST /sessions/auto.
ims.session-memory.continue_session
- Wrapper over POST /sessions/continue.
ims.session-memory.wrap_session
- Wrapper over POST /sessions/wrap.
ims.session-memory.list_open_sessions
- Wrapper over POST /sessions/list_open.
ims.session-memory.resume_session
- Wrapper over POST /sessions/resume.

For detailed behavior of these endpoints, see spec/API_ENDPOINTS.md in the integrated-memory-system repo and AGENTS.md in this repo for the IMS agent protocol.