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Firebase Docs MCP Server Setup

@nohe427

リポジトリ

基本情報

カテゴリ

メモリとナレッジ

ライセンス

Apache-2.0 license

トランスポート

stdio

作者

nohe427

Firebase Docs MCP Server Setup について

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

#firebase#mcp#server-setup

Firebase Docs MCP Server Setup の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

Firebase Docs MCP Server Setup のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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

よくある質問

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.

コメント

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