Firebase Docs MCP Server Setup

@nohe427

Repository

Basic information

About Firebase Docs MCP Server Setup

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 config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Firebase Docs MCP Server Setup tools

Tool list not available yet

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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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?

Set the Gemini API key: export genaikey="APIKEY".
From the docs-mcp folder, run go run . to index Firebase docs into $HOME/.indexResp/db.sqlite.
Copy the database to the docs-mcp-server folder: cp $HOME/.indexResp/db.sqlite ..
Install dependencies and build: npm ci && npm run build.
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

Frequently asked questions

What API key is required?

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

Where is the indexed database stored?

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

What transport does the MCP server use?

The server uses STDIO transport.

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.

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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