Marimo

A single MCP server that auto-discovers all running marimo notebooks and exposes tools for reading, editing, and running cells — no --mcp flag required.

Works with two backends:

• HTTP mode — connects to marimo notebooks running via marimo edit (standard server)
• VS Code mode — connects to marimo notebooks open in VS Code via the companion bridge extension

---

Architecture

Claude / MCP client
       │
       ▼
  marimo-mcp (Python MCP server)
       │
       ├─── HTTP backend ──────► marimo edit --no-token notebook.py
       │                         (port 2718 by default)
       │
       └─── VS Code backend ───► marimo-mcp-bridge (VS Code extension)
                                  │  port 42018
                                  ▼
                            vscode.commands.executeCommand('marimo.api', ...)
                                  │
                                  ▼
                          marimo VS Code extension

Discovery runs on every tool call (cached 5 s):

1. Scans running processes for marimo commands, extracts ports
2. For each port: fetches the HTML page to extract Marimo-Server-Token, then queries /api/home/running_notebooks
3. Checks if the bridge extension is running on port 42018 and appends any VS Code notebooks

VS Code backend — how cell execution works:

marimo's VS Code extension does not expose an HTTP server. The bridge extension (marimo-mcp-bridge) fills this gap — it runs a small HTTP server inside VS Code and forwards calls through VS Code's notebook execution pipeline (notebook.cell.execute → executeHandler → marimo LSP → kernel). This means edit_and_run_cell updates the cell visually in VS Code and returns actual stdout/stderr output.

VS Code backend — get_deps and get_variables:

These tools use static analysis of the .py file via marimo's own AST engine. No kernel or bridge needed — just the file on disk. get_variables returns variable names and their kinds (variable, import, function, class); values are only available via the HTTP backend with a running session.

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Installation

1. Python MCP server

Requires Python 3.11+ and uv.

git clone <repo>
cd marimo-mcp
uv sync          # creates .venv and installs all dependencies

2. VS Code bridge extension (for VS Code notebooks)

cd marimo-mcp-bridge
npm install
bash install.sh  # compiles TypeScript, packages as VSIX, installs in VS Code

After installing, reload VS Code window (Developer: Reload Window).

For subsequent updates after code changes, just run bash install.sh again.

---

Configuration

MCP settings

Add to .vscode/mcp.json or Claude Code's MCP config:

{
  "mcpServers": {
    "marimo": {
      "command": "uv",
      "args": ["run", "marimo-mcp"],
      "cwd": "/path/to/marimo-mcp",
      "env": {
        "MARIMO_TOKEN": "optional — only needed if marimo started with token auth"
      }
    }
  }
}

uv run automatically uses the .venv created by uv sync.

Token authentication

By default marimo generates a random access token. Either:

• Start marimo with --no-token to disable authentication, or
• Set MARIMO_TOKEN to the token from the startup URL (?access_token=...)

---

Tools

Tool	HTTP	VS Code	Description
list_notebooks	✓	✓	List all discovered notebooks
create_notebook	✓	✓	Create a new .py notebook file
get_cells	✓	✓	List cells with IDs and code
get_cell_outputs	✓	—	Visual output and console streams
get_errors	✓	—	All errors grouped by cell
get_variables	✓ (with values)	✓ (names/kinds only)	Variables in the notebook
get_deps	✓	✓	Cell dependency graph
add_cell	✓	✓	Add a new cell (not executed); cell_type="markdown" for markup
edit_and_run_cell	✓	✓	Edit a cell and run it, returns stdout/stderr
delete_cell	✓	✓	Delete a cell

get_cell_outputs and get_errors return an explicit error for VS Code notebooks. Use edit_and_run_cell with print() calls to inspect values.

add_cell parameters

add_cell(notebook, code, after_cell_id=None, cell_type="code")

• cell_type="code" — standard Python cell (default)
• cell_type="markdown" — markdown cell; in VS Code uses native NotebookCellKind.Markup (renders immediately without execution); in HTTP mode wraps in mo.md(...)

Current limitations

• VS Code output is stdout/stderr only — rich outputs (plots, dataframes, marimo UI elements) are not captured via the bridge. Use the HTTP backend (marimo edit --no-token) for full output access.

---

Claude Code skill

A Claude Code skill for working with this MCP server is available at ~/.claude/plugins/marketplaces/marimo-mcp/SKILL.md. It's enabled automatically when the marimo-mcp@marimo-mcp plugin is active in your Claude Code settings.

This skill is complementary to marimo-pair (which handles marimo edit HTTP mode). Use marimo-mcp when the notebook is open in VS Code.

---

Testing guide

Test 1: HTTP backend (marimo running locally)

Start a notebook:

marimo edit --no-token --port 2718 /tmp/test_notebook.py

Verify discovery:

uv run python -c "
import asyncio
from marimo_mcp.discovery import discover_notebooks
async def main():
    nbs = await discover_notebooks()
    for nb in nbs:
        print(f'{nb.name}  port={nb.port}  via={\"vscode\" if nb.is_lsp else \"http\"}')
asyncio.run(main())
"

Edit and run a cell:

import asyncio
from marimo_mcp.server import get_cells, edit_and_run_cell

async def main():
    cells = await get_cells('test_notebook.py')
    # get a cell_id from the output
    result = await edit_and_run_cell('test_notebook.py', 'CELL_ID', 'x = 6 * 7\nprint(x)')
    print(result)  # {"output": "42", "stdout": "42\n", ...}

asyncio.run(main())

---

Test 2: VS Code bridge extension

Verify bridge is running:

curl -s http://127.0.0.1:42018/health
# {"status":"ok"}

List open VS Code notebooks:

curl -s http://127.0.0.1:42018/notebooks | python3 -m json.tool

Full round-trip (edit + run + get output):

import asyncio
from marimo_mcp.server import get_cells, edit_and_run_cell

async def main():
    cells = await get_cells('goyda.py')  # VS Code notebook
    cell_id = ...  # from cells output
    result = await edit_and_run_cell('goyda.py', cell_id, 'print(6 * 7)')
    print(result)  # {"output": "42", "stdout": "42\n", "stderr": ""}

asyncio.run(main())

---

Test 3: Unit tests

uv run pytest tests/ -v

25 tests should pass, covering MarimoClient, discovery logic, and notebook creation.

---

Troubleshooting

No notebooks found, but marimo is running:

• Run with --no-token, or set MARIMO_TOKEN
• Confirm the port is accessible: curl http://localhost:2718/

Bridge not available (connection refused on port 42018):

• Check the VS Code Output panel for "marimo-mcp-bridge" channel
• Make sure a .py marimo notebook is open — the marimo.api command is only available when the marimo extension is active

Bridge needs reinstalling after code changes:

cd marimo-mcp-bridge
bash install.sh
# Then: Developer: Reload Window in VS Code

edit_and_run_cell returns empty output or times out (VS Code):

The cell execution uses VS Code's notebook pipeline. If it times out (15s default):

1. Check VS Code Output → marimo for kernel startup errors
2. Make sure the notebook is open and visible (not just in the background)
3. Try running a cell manually first to warm up the kernel

Wrong Python executable (kernel fails to start):

The bridge resolves Python in this order:

1. .venv/bin/python next to the notebook file
2. .venv/bin/python in any VS Code workspace folder
3. VS Code Python extension active environment
4. python3 (system fallback)

Create a .venv with marimo in the workspace root:

python3 -m venv .venv
.venv/bin/pip install marimo