Turn Your AI Assistant Into a Coda Power User

Stop switching between your AI chat and Coda when you're deep in a flow state. This MCP server connects your AI assistant directly to Coda's API, letting you create, edit, and manage your documents without breaking context.

The Friction Problem

You're architecting a feature, working through complex logic with Claude or Cursor. You need to document your decisions, update project specs, or create new pages for different components. But every time you need to touch Coda, you're alt-tabbing away, losing your train of thought, and manually recreating context.

That context switching kills productivity. This MCP server eliminates it entirely.

What You Get

Nine powerful tools that turn your AI assistant into a Coda native:

• Document Management: List and navigate your Coda workspace
• Page Operations: Create, read, update, duplicate, and rename pages
• Content Control: Replace entire pages, append content, or peek at specific sections
• Hierarchical Structure: Create subpages and organize complex documentation trees
• Markdown Native: Everything works with markdown, so your AI can generate properly formatted content

Real-World Workflows

Technical Spec Generation: "Create a new page called 'User Authentication Service' under the Backend Architecture section. Include the API endpoints, data models, and security considerations we just discussed."

Meeting Documentation: "Append today's standup notes to the Sprint 23 page, then create individual pages for each of the three blockers we identified."

Knowledge Base Maintenance: "Review our troubleshooting guide and update the database connection issues section with the new debugging steps we developed."

Project Planning: "Duplicate the 'Feature Template' page and set it up for the notification system feature, then update the requirements based on our discussion."

Integration Takes 30 Seconds

Add to your MCP client config:

{
  "mcpServers": {
    "coda": {
      "command": "npx",
      "args": ["-y", "coda-mcp@latest"],
      "env": {
        "API_KEY": "your-coda-api-key"
      }
    }
  }
}

That's it. No complex setup, no dependency hell. Just grab your API key from Coda settings and you're running.

Prefer Docker? Same simple config with docker run instead of npx.

Why This Matters

Your AI assistant already understands your codebase, your architecture decisions, and your project context. Now it can act on that understanding directly in your documentation system. No more losing momentum to manual document updates. No more forgetting to document important decisions because switching contexts felt like too much overhead.

This is about keeping your AI assistant and your documentation in sync with your actual work, automatically, without thinking about it.

When your AI can read your existing specs, create new pages, and update documentation as you discuss changes, you're not just saving time—you're ensuring your documentation actually stays current with your development process.