millimap-mcp

MCP (Model Context Protocol) server that lets Claude Desktop read the active MilliMap session — its dataset, clusters, cell-type annotations, marker genes, regions of interest — and drive analyses inside the viewer from chat.

How it works

┌──────────────────┐       writes        ┌──────────────────────────┐
│  MilliMap        │  ──────────────▶    │  ~/.millimap/            │
│  (desktop app)   │     every 3s        │  mcp_session.json        │
└──────────────────┘                     └──────────────────────────┘
                                                    │ reads
                                                    ▼
                                         ┌──────────────────────────┐
┌──────────────────┐     stdio MCP       │  millimap-mcp            │
│  Claude Desktop  │  ◀───────────────▶  │  (this package)          │
└──────────────────┘                     └──────────────────────────┘

MilliMap writes a snapshot of its current session to ~/.millimap/mcp_session.json every few seconds. This MCP server is launched by Claude Desktop as a stdio subprocess; it reads the snapshot and exposes it to Claude as MCP resources and tools.

Prerequisites

• MilliMap installed and runnable — see milliomics/MilliMap.

• Claude Desktop — download from anthropic.com.

• Python 3.10+ with pip.

Install — into your existing MilliMap environment

Important: install millimap-mcp into the same Python environment you use to run MilliMap. That way the resulting millimap-mcp script lands in that env's bin/ (or Scripts\ on Windows), and Claude Desktop finds it automatically when you activate the env.

If you set up MilliMap with conda (the recommended path)

# 1. Activate the MilliMap env FIRST — this is the step people miss.
conda activate millimap

# 2. Clone this repo somewhere convenient.
git clone https://github.com/milliomics/millimap-mcp.git
cd millimap-mcp

# 3. Install into the activated env.
pip install -e .

If you set up MilliMap with pip (no conda)

Use the same Python you use to launch MilliMap. The safest invocation is to spell out the interpreter explicitly:

git clone https://github.com/milliomics/millimap-mcp.git
cd millimap-mcp

# Replace this with the python you use for MilliMap:
/path/to/your/python -m pip install -e .

# e.g.:
# /usr/local/bin/python3.11 -m pip install -e .
# or:
# /Users/you/venvs/millimap/bin/python -m pip install -e .

Verify the install

After install, the millimap-mcp script should be on your PATH (when the env is activated):

which millimap-mcp           # macOS / Linux
where millimap-mcp           # Windows

You should see a path under your MilliMap env, e.g.:

• conda: /Users/<you>/anaconda3/envs/millimap/bin/millimap-mcp

• venv: /Users/<you>/venvs/millimap/bin/millimap-mcp

• Windows conda: C:\Users\<you>\anaconda3\envs\millimap\Scripts\millimap-mcp.exe

Keep that path handy — you'll paste it into Claude Desktop's config in the next step (or just use the bare name millimap-mcp if Claude Desktop sees the same PATH you do).

Wire it up to Claude Desktop

Open Claude Desktop's config file:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

• Windows: %APPDATA%\Claude\claude_desktop_config.json

• Linux: ~/.config/Claude/claude_desktop_config.json

Create the file if it doesn't exist. Add (merge into any existing mcpServers object):

{
  "mcpServers": {
    "millimap": {
      "command": "millimap-mcp"
    }
  }
}

Use an absolute path if millimap-mcp isn't on Claude Desktop's PATH

Claude Desktop launches subprocesses with its own PATH, which may not include your conda env's bin/. If you get "command not found" / "spawn ENOENT" after restarting Claude, swap the bare command for the absolute path you got from which millimap-mcp above:

{
  "mcpServers": {
    "millimap": {
      "command": "/Users/<you>/anaconda3/envs/millimap/bin/millimap-mcp"
    }
  }
}

On Windows, double-escape backslashes (JSON requires it):

{
  "mcpServers": {
    "millimap": {
      "command": "C:\\Users\\<you>\\anaconda3\\envs\\millimap\\Scripts\\millimap-mcp.exe"
    }
  }
}

Then fully quit + relaunch Claude Desktop (the window-close X is not enough — quit from the menu bar / system tray).

In Claude Desktop's tools menu (plug icon in the message composer) you should now see millimap. Toggle it on.

What Claude can see

Resources (read-only context):

• millimap://session — dataset name, cell/gene counts, assay, cluster column

• millimap://clusters — cluster IDs and sizes

• millimap://annotations — cluster → cell-type labels set by the scientist

• millimap://markers — top marker genes per cluster

• millimap://rois — regions of interest saved in the session

• millimap://analysis_cards — workspace result cards (summaries only — use get_analysis_card for the full payload)

Read tools (read the snapshot, no side effects):

• get_cluster_markers(cluster_id, top_n) — markers for one cluster

• genes_for_cell_type(cell_type) — "what genes mark T cells?"

• search_genes(query, limit) — find which cluster a gene marks

• list_rois() — enumerate saved ROIs

• list_analysis_cards() — workspace result cards (summaries)

• get_analysis_card(card_id, max_rows) — full payload of one card including its DataFrame

Write tools (drive MilliMap's analysis library + UI):

• run_clustering(resolution, n_neighbors) — re-cluster the dataset

• find_markers(groupby, method) — run rank_genes_groups

• annotate_cluster(cluster_id, label) — assign a cell-type label

• score_gene_signature(genes, score_name) — score a gene set across cells

• apply_qc_filter(min_genes, max_genes, min_counts, max_mito_pct) — QC filter

• run_millimap_tool(tool_name, tool_args_json) — escape hatch for any of MilliMap's 30+ analysis tools (DE, GO enrichment, neighborhood enrichment, co-occurrence, Ripley, doublet detection, dotplot/heatmap/violin, etc.)

Write tools require MilliMap to be running with a dataset loaded. They POST to a local HTTP endpoint (127.0.0.1, ephemeral port) served by the viewer; the port is discovered via ~/.millimap/mcp_control.json.