marimo-mcp
Related Servers
Alternatives to marimo-mcp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityBmaintenanceEnables inspecting and editing live marimo notebooks via a FastMCP server, offering tools for managing cells, variables, and execution.14MIT
- AlicenseNot gradedqualityCmaintenanceExposes Jupyter notebook operations as MCP tools over plain HTTP, allowing AI agents to explore, edit, run, and debug notebooks in a live VS Code session using local or remote kernels.2MIT
- AlicenseNot gradedqualityDmaintenanceExposes VSCode Jupyter notebooks to MCP-compatible AI agents, enabling them to read, edit, and run cells against the same kernel.MIT
- AlicenseNot gradedqualityBmaintenanceEnables external agents to run, edit, create, and manage the Jupyter notebook the user is actively editing in VS Code, headlessly and without approval dialogs. Works with any MCP client and is Jupyter-optional for document operations.1MIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that gives any MCP-compatible LLM client full control over a live JupyterLab instance.MIT
- AlicenseNot gradedqualityAmaintenanceVS Code extension that bridges local Jupyter Notebooks with AI Agents via MCP, enabling direct control of the active notebook tab.2MIT
TDQS
Scored across 10 tools
Each tool targets a distinct operation: notebook creation, cell manipulation (add, delete, edit/run), and retrieval of cells, outputs, deps, errors, variables, and running notebooks. No functional overlap.
All tool names follow a clear verb_noun pattern in snake_case (e.g., `create_notebook`, `get_cells`). Minor length variation does not break consistency.
10 tools cover the essential CRUD and inspection workflows for marimo notebooks. The count is well-scoped for a focused MCP server.
The set covers core notebook lifecycle (create, list, add/delete/edit/run cells) and introspection (cells, outputs, errors, dependencies, variables). Missing operations like save, rename, or reorder cells, but not critical for typical agent tasks.