firebase-docs-mcp

firebase-docs-mcp

3.2
ai_chatbotknowledge_and_memorycloud_platforms

If you are the rightful owner of firebase-docs-mcp and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

The Firebase Docs MCP Server Setup involves indexing Firebase documents and serving them over a model context protocol server using a stdio transport.

The Firebase Docs MCP Server Setup is a comprehensive solution for indexing and serving Firebase documentation using a Model Context Protocol (MCP) server. The setup involves three main components: the docs-mcp indexer, the docs-mcp-server, and the genkit-mcp-tester. The docs-mcp indexer is a Go project that fetches and indexes Firebase documents, storing them in a SQLite database. The docs-mcp-server serves the indexed content over a stdio transport, allowing for efficient retrieval and interaction. The genkit-mcp-tester is a client implementation used to test the server's functionality. The setup requires an API key from AI Studio to use the Gemini embedding model for document processing. The process involves setting up the environment, running the indexer, and testing the server using the provided tools. The setup is designed to be robust, with retry strategies for indexing failures and a user-friendly interface for testing and interaction.

Features

  • Efficient Document Indexing: Uses a Go project to index Firebase documents and store them in a SQLite database.
  • Stdio Transport Server: Serves indexed content over a stdio transport for efficient retrieval.
  • Genkit Client Testing: Includes a genkit implementation for testing the server's functionality.
  • API Key Integration: Utilizes the Gemini embedding model with an API key from AI Studio for document processing.
  • User-Friendly Interface: Provides a user-friendly interface for testing and interaction with the server.

Tools

  1. find-firebase-doc

    Tool for finding and retrieving Firebase documentation using the MCP server.

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