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Firebase Docs MCP Server Setup

@nohe427

基本信息

分类

记忆与知识

许可证

Apache-2.0 license

传输方式

stdio

作者

nohe427

关于 Firebase Docs MCP Server Setup

This is a sample for showing how to do FIrebase Docs as an MCP server (including indexing documents)

Firebase Docs MCP Server Setup 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块,请前往代码仓库查看安装说明。

代码仓库

Firebase Docs MCP Server Setup 工具

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当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Firebase Docs MCP Server Setup?

Firebase Docs MCP Server Setup is a toolchain that indexes Firebase documentation into a local SQLite database and serves the indexed content through a Model Context Protocol (MCP) server using stdio transport. It is designed for developers who want to query Firebase documentation via MCP-compatible AI assistants or tools. The project includes a Go-based indexer, a Node.js MCP server, and a Genkit-based MCP client for testing.

How to use Firebase Docs MCP Server Setup?

  1. Set the Gemini API key: export genaikey="APIKEY".
  2. From the docs-mcp folder, run go run . to index Firebase docs into $HOME/.indexResp/db.sqlite.
  3. Copy the database to the docs-mcp-server folder: cp $HOME/.indexResp/db.sqlite ..
  4. Install dependencies and build: npm ci && npm run build.
  5. Test the MCP server: npx @modelcontextprotocol/inspector node build/index.js (or use the Genkit tester via npx genkit start -- npx tsx --watch src/index.ts).

Key features of Firebase Docs MCP Server Setup

  • Indexes multiple Firebase documentation pages into a local SQLite database
  • Uses Gemini embedding models for document retrieval
  • Provides a stdio-based MCP server for tool-based queries
  • Includes a Genkit MCP client for interactive testing
  • Implements retry logic on indexing failures

Use cases of Firebase Docs MCP Server Setup

  • Querying Firebase documentation through an AI assistant using MCP tools
  • Building a custom documentation retrieval pipeline for Firebase content
  • Testing and debugging an MCP server with a local Genkit DevUI
  • Integrating Firebase docs into Genkit flows via the find-firebase-doc tool

常见问题

1

What API key is required?

A Gemini API key from AI Studio is required — set it with the `genaikey` environment variable.

2

Where is the indexed database stored?

The SQLite database is stored at `$HOME/.indexResp/db.sqlite`.

3

What transport does the MCP server use?

The server uses STDIO transport.

4

Are there any known issues with running the inspector?

The author reports trouble using the VSCode integrated terminal for the inspector; use your system terminal instead.

5

What dependencies are needed?

Go, Node.js, npm, and Genkit are required. The indexer uses Go and the server uses Node.js.

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