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The MCP server is currently in beta. We’d love your feedback at [email protected].
When your AI coding assistant tries to understand your codebase to build a feature, it often has to do significant work to figure out how things connect — and may not do it as thoroughly as a dedicated analysis would. cubic’s AI wiki solves this by pre-computing that understanding — spending significant reasoning and tokens to analyze your codebase and distill it into structured documentation. The MCP server gives AI assistants like Cursor, Claude, Windsurf, and OpenCode direct access to this cached knowledge — so they can query pre-synthesized context instead of figuring it out from scratch. With auto-refresh enabled, this stays up to date as your codebase evolves. Integrations page showing MCP Server card in Settings

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What you can do

Once connected, your AI assistant can:
  • Access AI Wikis - Query AI-generated codebase documentation containing architecture overviews, feature explanations, and code references
  • Explore repositories - Discover and navigate wiki pages for any repository in your installation
  • Understand codebases - Get contextual information about how systems work, design patterns, and component relationships
The MCP server requires a cubic account with access to at least one repository. You must be a member of the repository’s installation to access its wiki.

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Quick setup

1

Generate an API key

Go to Settings → Integrations → MCP Configuration and click Generate API Key. Copy the key immediately—it’s only shown once.MCP Server configuration showing API key and client setup
2

Configure your AI client

Add the cubic MCP server to your preferred AI coding assistant using the configuration below.
3

Start using wiki tools

Ask your AI assistant to list wiki pages or get specific documentation for your repositories.

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Client configuration

Add to ~/.cursor/mcp.json:
{
  "mcpServers": {
    "cubic": {
      "url": "https://cubic.dev/api/mcp",
      "headers": {
        "Authorization": "Bearer cbk_your_api_key_here"
      }
    }
  }
}
Restart Cursor after adding the configuration for changes to take effect.

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Available tools

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Wiki tools

cubic AI Wikis are AI-generated codebase documentation containing architecture overviews, feature explanations, code references, and diagrams. Use these tools to explore and understand codebases.
Enable auto-refresh on your wiki to keep documentation up to date as your codebase evolves.
ToolDescriptionParameters
list_wiki_pagesList all available wiki pages for a repositoryowner, repo
get_wiki_pageRetrieve the content of a specific wiki pageowner, repo, pageRef
Recommended workflow:
  1. Call list_wiki_pages to discover available documentation for a repository
  2. Use get_wiki_page with a page reference to read specific content
Ask your AI assistant:
“List the wiki pages for the acme/backend repository”
The assistant will call list_wiki_pages and return something like:
Available wiki pages for acme/backend:
- architecture-overview
- authentication-system
- database-schema
- api-endpoints
- deployment-guide
Then ask:
“Show me the authentication system documentation”
The assistant will call get_wiki_page with pageRef: "authentication-system" and return the full documentation.

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Troubleshooting

Verify that:
  • Your API key is correct and hasn’t been revoked
  • You’re using the correct endpoint: https://cubic.dev/api/mcp
  • Your firewall or network allows outbound HTTPS connections
  • Check that your API key is prefixed with cbk_ - Ensure the Authorization header uses Bearer format - Regenerate your API key if issues persist
  • Confirm the repository has an AI Wiki generated - Verify you have access to the repository’s installation - Check that the owner and repo parameters match the GitHub repository exactly
  • Restart your AI client after updating the configuration
  • Check the config file path is correct for your operating system
  • Validate your JSON syntax (no trailing commas, proper quoting)

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What’s next?

We’re considering adding more tools to the MCP server:
  • PR review tools - Access AI review comments and suggestions
  • Codebase search - Search across your indexed repositories
  • Analytics access - Query review metrics and team insights
Interested in any of these? Let us know — your feedback helps us prioritize.