mcp-coda
llms.txt2 starsChanged 8 months agoMITView on GitHub
MCP server for the Coda API. It provides 54 tools, 12 resources, and 5 prompts for docs, pages, tables, rows, formulas, controls, permissions, folders, publishing, automations, and analytics. mcp-coda is an MCP server that wraps the Coda REST API v1. It gives an AI assistant CRUD access to all Coda resource types, live and static context, and prompt templates for common workflows. It implements the MCP 2026-07-28 specification (MCP 2.0) and stays compatible with 2025-11-25 clients. It uses FastMCP 4.x,…
- Installs packages
Files
# mcp-coda > MCP server for the Coda API. It provides 54 tools, 12 resources, and 5 prompts for docs, pages, tables, rows, formulas, controls, permissions, folders, publishing, automations, and analytics. mcp-coda is an MCP server that wraps the Coda REST API v1. It gives an AI assistant CRUD access to all Coda resource types, live and static context, and prompt templates for common workflows. It implements the MCP 2026-07-28 specification (MCP 2.0) and stays compatible with 2025-11-25 clients. It uses FastMCP 4.x, httpx, and Pydantic. - **Install**: `uvx mcp-coda` - **Version**: 0.12.3 - **Python**: >=3.10 - **License**: MIT - **MCP protocol**: 2026-07-28 (MCP 2.0); compatible with 2025-11-25 clients - **Transport**: stdio (default), streamable-http (recommended for remote); sse (deprecated by MCP 2026-07-28, still works) - **Read-only mode**: `MCP_READ_ONLY=true` (or `CODA_READ_ONLY=true`) hides the 20 write tools and write-workflow prompts for the life of the process; any non-false value locks; set it in the deployer's env - **Registry**: `io.github.vish288/mcp-coda` - **Required env vars**: `CODA_API_TOKEN` (also accepts `CODA_TOKEN` or `CODA_PAT`) - **Optional env vars**: `CODA_READ_ONLY` / `MCP_READ_ONLY`, `CODA_BASE_URL` (API base), `CODA_TIMEOUT` (request timeout), `CODA_HTTP_BEARER_TOKEN` (required to bind an HTTP transport to a non-loopback host; min 16 chars) ## Documentation - [README](https://github.com/vish288/mcp-coda#readme): canonical reference for setup, env vars, all 54 tools, 12 resources, 5 prompts - [PyPI](https://pypi.org/project/mcp-coda/): install via `pip install mcp-coda` or `uvx mcp-coda` - [GitHub](https://github.com/vish288/mcp-coda): source code, issue tracker, development setup - [MCP Registry](https://registry.modelcontextprotocol.io): discover and install MCP servers ## Optional - [Changelog](https://github.com/vish288/mcp-coda/releases): per-version release notes with breaking changes - [MCP Specification](https://modelcontextprotocol.io/docs): protocol spec for tools, resources, and prompts - [FastMCP](https://github.com/jlowin/fastmcp): Python framework this server is built on - [Coda API Reference](https://coda.io/developers/apis/v1): upstream REST API that this server wraps
In this repository2 other files it gives its agents.
- AGENTS.mdAGENTS.md
- llms-full.txtllms.txt
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

