This server implements the Model Context Protocol (MCP) to act as a bridge between a Large Language Model (LLM) like Claude and Firebase (Firestore).
MCP Firebase Server MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. This server implements the Model Context Protocol (MCP) to act as a bridge between a Large Language Model (LLM) like Claude and Firebase (Firestore). It allows the LLM to read from and write to Firestore collections by exposing these.
You will need 2 environment variables: SERVICE_ACCOUNT_KEY_PATH, FIREBASE_STORAGE_BUCKET. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
asynccontextmanager and full type hinting features used by MCP) * Pip (Python package installer) or uv (recommended by MCP docs for project management) * A Firebase project with Firestore enabled. * A Firebase service account key JSON file.Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. It is maintained by davo20019; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
{
"mcpServers": {
"firebase": { // A unique name you assign to this server instance in the client's config
"command": "/full/path/to/your/mc-firebase-server/run_server.sh", // IMPORTANT: Use the absolute path to the script
"args": [], // Typically empty if run_server.sh handles everything
// "cwd": "/full/path/to/your/mc-firebase-server/", // Usually not needed if run_server.sh cds to its own dir
"env": {
// Replace with the ACTUAL absolute path to your service account key file
"SERVICE_ACCOUNT_KEY_PATH": "/path/to/your/serviceAccountKey.json",
// Optional: Replace with your actual Firebase Storage bucket name if needed by future tools
"FIREBASE_STORAGE_BUCKET": "your-project-id.appspot.com"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
asynccontextmanager and full type hinting features used by MCP) * Pip (Python package installer) or uv (recommended by MCP docs for project management) * A Firebase project with Firestore enabled. * A Firebase service account key JSON file.| Variable | Description | Required |
|---|---|---|
| SERVICE_ACCOUNT_KEY_PATH | Credential the server authenticates with. | Yes |
| FIREBASE_STORAGE_BUCKET | Configuration value read at startup. | Optional |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.