What API key is required?
A Gemini API key from AI Studio is required — set it with the `genaikey` environment variable.
@nohe427
Basic information
This is a sample for showing how to do FIrebase Docs as an MCP server (including indexing documents)
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
export genaikey="APIKEY".docs-mcp folder, run go run . to index Firebase docs into $HOME/.indexResp/db.sqlite.docs-mcp-server folder: cp $HOME/.indexResp/db.sqlite ..npm ci && npm run build.npx @modelcontextprotocol/inspector node build/index.js (or use the Genkit tester via npx genkit start -- npx tsx --watch src/index.ts).find-firebase-doc toolA Gemini API key from AI Studio is required — set it with the `genaikey` environment variable.
The SQLite database is stored at `$HOME/.indexResp/db.sqlite`.
The server uses STDIO transport.
The author reports trouble using the VSCode integrated terminal for the inspector; use your system terminal instead.
Go, Node.js, npm, and Genkit are required. The indexer uses Go and the server uses Node.js.

Model Context Protocol Servers
Memlord is a remote MCP server available at https://app.memlord.com.

Local AI agent for your Mac with a built-in MCP server: 18 tools for your notes and PDFs, a temporal memory graph, an on-device LLM and a neural voice. No account, no telemetry. No data centers required.
Groundwork: company memory for your AI tools. Docs public. Source closed. Public proof needs no account.

The official Semantic-UI-React integration
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