memsearch-mcp
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Here is a step-by-step guide with screenshots.
memsearch-mcp
FastMCP server wrapping the memsearch semantic memory search library. Exposes hybrid vector+BM25+reranker search and index-refresh tools to forge agents over streamable-http MCP transport.
Overview
Agent memory on forge lives in markdown files across a three-tier hierarchy: session (per-project
plugin dirs), working (~/.claude/memory/), and docs. memsearch-mcp lets agents query all of
it with a single tool call — without reading files directly or knowing where they live.
Who uses it: All 5 forge resident agents (research, developer, writer, security, sysadmin)
have memsearch-mcp in their scoped-mcp manifests. index_memory is denylisted for security,
research, and writer.
Tools
Tool | Description | Key Parameters | Returns |
| Hybrid vector+BM25+reranker search over Milvus-indexed agent memory |
|
|
| Trigger a memsearch index refresh for a path or default to |
|
|
search_memory result fields
Field | Type | Description |
|
| Absolute path to the source file |
|
| Relevance score (higher = more relevant) |
|
| Matching text chunk |
|
| Nearest markdown heading above the chunk |
|
|
|
|
| First line of the chunk in the source file |
|
| Last line of the chunk |
index_memory path restrictions
index_memory accepts only paths under:
~/.claude/memory/~/.claude/projects//opt/agents/memory/
Requests outside these roots are rejected with an error (not forwarded to the library).
Environment Variables
Variable | Required | Default | Purpose |
| No |
| Port for the streamable-http server |
| No |
| structlog log level |
| No | (library default) | Path to memsearch config file |
Installation
Requires Python 3.11+ and an existing memsearch venv with the memsearch library installed.
# From the memsearch venv (forge standard)
/opt/venvs/memsearch/bin/pip install -e /home/ted/repos/personal/memsearch-mcp
# Or from git
/opt/venvs/memsearch/bin/pip install "git+https://github.com/TadMSTR/memsearch-mcp.git"Dependencies
fastmcp>=2.0pydantic>=2.0structlog>=24.0memsearch(must be installed in the same venv — not in PyPI, install from source)
Deployment
PM2
ecosystem.config.js in the repo root:
module.exports = {
apps: [{
name: "memsearch-mcp",
script: "/opt/venvs/memsearch/bin/python3",
args: ["-m", "memsearch_mcp.server"],
cwd: "/home/ted/repos/personal/memsearch-mcp",
interpreter: "none",
env: {
LOG_LEVEL: "INFO",
MEMSEARCH_MCP_PORT: "8493",
},
}]
};pm2 start ecosystem.config.js
pm2 savescoped-mcp wiring
Add to each agent manifest at ~/.claude/manifests/<agent>-agent.yml:
modules:
- name: memsearch-mcp
type: mcp_proxy
url: "http://127.0.0.1:8493/mcp"
tool_denylist:
- "index_memory" # omit for developer and sysadminNo restart of scoped-mcp is needed — manifests are loaded fresh on each agent session start.
Observability
Logs are written to ~/logs/memsearch-mcp.log (stdout + stderr merged, timestamped by PM2).
Log lines are JSON (structlog):
{"event": "search_memory", "query": "grafana dashboard", "limit": 10, "level": "info"}
{"event": "search_memory_done", "query": "grafana dashboard", "results": 7, "level": "info"}
{"event": "index_memory_dir_done", "path": "/home/ted/.claude/memory", "chunks": 412, "level": "info"}Tool arguments are not included in logs — only query strings and result counts.
To check server health:
pm2 status memsearch-mcp
curl -s http://127.0.0.1:8493/mcp | head -5 # should return SSE headers or MCP handshakeThis server cannot be installed
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