Coda MCP Server Integration

What does “Coda” MCP Server do?

The Coda MCP (Model Context Protocol) Server is a standardized, universal API server that connects AI assistants with Coda’s suite of tools and services. By implementing the MCP specification, the Coda MCP Server enables AI clients to interact programmatically with Coda, facilitating tasks such as querying documents, automating workflows, and managing files or data within the Coda ecosystem. This allows developers to build enhanced development workflows, integrate contextual data into LLM interactions, and orchestrate actions across external systems using a unified protocol. The server is built to ensure compatibility with other MCP-compliant services, making it a valuable bridge between AI agents and Coda’s powerful platform.

List of Prompts

No information about prompt templates was found in the available repository files.

List of Resources

No explicit MCP resources are documented or listed in the available files.

List of Tools

For the complete list of available tools, the documentation refers to src/universal_mcp_coda/README.md. However, the content of this file is not available in the provided information, so tool details cannot be listed.

Use Cases of this MCP Server

• The available documentation does not provide specific use cases or example workflows for the Coda MCP Server.*

How to set it up

Windsurf

1. Ensure Python 3.11+ and uv are installed.
2. Sync project dependencies:

   uv sync
   

3. Activate the virtual environment:
   • Linux/macOS: source .venv/bin/activate
   • Windows: .venv\Scripts\Activate
4. Start the MCP Inspector:

   mcp dev src/universal_mcp_coda/server.py
   

5. Install the application:

   mcp install src/universal_mcp_coda/server.py
   

JSON Configuration Example: Not provided in the available documentation.

Securing API Keys: No examples or instructions found.

Claude

No setup instructions specific to Claude are provided.

Cursor

No setup instructions specific to Cursor are provided.

Cline

No setup instructions specific to Cline are provided.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "coda": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “coda” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the available documentation, Coda MCP provides a basic overview and some local setup instructions, but lacks detailed resources, prompt templates, explicit tool listings, and security guidance. It appears to be in an early or under-documented state.

Our opinion

The Coda MCP repository currently lacks critical documentation on resources, tools, prompts, and security, which significantly limits its usability and discoverability. Based on the above tables, we would rate this MCP server a 2/10, as it shows intent and minimal setup guidance but fails to deliver the comprehensive detail expected of a production-ready MCP implementation.

MCP Score