Antigravity Ai Directory Firebase Mcp

Created By
7 months ago
Build apps with Firebase Authentication, Firestore, Storage, and more. Real-time synchronization and serverless backend.
Overview

What is Antigravity AI Directory - Firebase MCP?

Antigravity AI Directory - Firebase MCP is a platform that allows developers to build applications using Firebase services such as Authentication, Firestore, and Storage, providing real-time synchronization and a serverless backend.

How to use Antigravity AI Directory - Firebase MCP?

To use this platform, create a Firebase project, generate a service account key, download the JSON key file, and add the credentials to your configuration.

Key features of Antigravity AI Directory - Firebase MCP?

  • Real-time database capabilities
  • Serverless architecture
  • Easy integration with Firebase services

Use cases of Antigravity AI Directory - Firebase MCP?

  1. Building web and mobile applications with real-time data updates.
  2. Implementing user authentication and data storage solutions.
  3. Creating scalable applications without managing server infrastructure.

FAQ from Antigravity AI Directory - Firebase MCP?

  • What services does Firebase MCP support?

Firebase MCP supports various Firebase services including Authentication, Firestore, and Storage.

  • Is there a cost associated with using Firebase MCP?

Firebase MCP is free to use, but Firebase services may have associated costs based on usage.

Server Config

{
  "mcpServers": {
    "firebase": {
      "env": {
        "FIREBASE_PROJECT_ID": "your_project_id",
        "FIREBASE_PRIVATE_KEY": "your_service_account_key"
      },
      "args": [
        "-y",
        "@firebase/mcp-server"
      ],
      "command": "npx"
    }
  }
}
Project Info
Created At
7 months ago
Updated At
7 months ago
Author Name
-
Star
-
Language
-
License
-

Recommend Servers

View All
//beforeyouship — LLM Cost Modeling From Your Editor
@Indiegoing

Query realistic LLM cost models without leaving your editor. beforeyouship models the **true monthly cost** of an LLM app architecture — retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth — across GPT-5.x, Claude, Gemini, DeepSeek, and more. Not a token calculator: a planning tool for the design phase, before you commit to a stack. **No API key needed to try it** — demo mode covers the six free-tier models. A Pro key from [beforeyouship.dev](https://beforeyouship.dev) unlocks the full 18-model catalog. ## What you can ask - "How much will a RAG chatbot cost at 10,000 requests/day?" - "Compare Claude Haiku vs Gemini Flash pricing for my workload" - "What's the cheapest model for a multi-step agent at scale?" - "Show me current per-token prices for Anthropic models" ## Tools ### `estimate_cost` Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case monthly cost per model, 3×/10× growth scenarios, and an opinionated recommendation with reasoning. ### `get_model_prices` Current per-1M-token pricing — input, output, cached input, batch — with context windows and staleness metadata. ### `list_archetypes` Seven preset architecture patterns (simple chatbot, chatbot with history, RAG pipeline, multi-model router, coding assistant, document processor, multi-step agent) used as starting points for estimates. ## Setup **Claude Code:** ​```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ​``` **Cursor / other clients** — add a remote server: ​```json { "mcpServers": { "beforeyouship": { "type": "streamable-http", "url": "https://beforeyouship.dev/api/mcp" } } } ​``` Add an `Authorization: Bearer bys_...` header with a Pro key for the full catalog. ## Try it > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day

5 hours ago
Mnemom

7 hours ago