"Firebase: Backend Platform for App Development" matching MCP servers:

Enables interaction with Firebase projects and services, including deployment, database management, authentication, and local emulation, through natural language.

Auto-generated MCP server that enables interaction with the Firebase App Distribution API, allowing users to manage distribution of pre-release app builds to testers through natural language commands.

A bridge that enables Large Language Models to read from and write to Firebase Firestore collections through Model Context Protocol (MCP) tools.

A FastMCP-powered server for accessing curated travel spot data from a PostgreSQL database. It provides tools to retrieve major attractions, supporting sites, and the top ten most popular destinations.

Enables AI assistants to discover, retrieve, and compare official international development indicators from sources such as the World Bank, FAOSTAT, WHO, UNICEF, and IMF, while preserving source identifiers, units, and citations.

A Model Context Protocol server that enables seamless integration between Claude AI and development tools like VSCode, Augment, Vercel, Airtable, and Square.

A shared communication bus for multiple agents using NATS and MCP, enabling MCP clients to list, message, and query agents.

Enables app intelligence across Google Play and the Apple App Store, including details, reviews, and search via a unified API.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.

An MCP server that provides live status updates for the Eco via Sirens game server, displaying meteor countdowns, player statistics, and world information directly within Claude Desktop. It also serves as a minimal reference implementation for building MCP Apps in Python without complex tooling.

An MCP server for internal data platforms that enables search, viewing, tracing, and read-only querying of business assets like dashboards, metrics, and events.

Enables MCP-compatible AI clients to interpret the init-app CLI, explore its supported blueprints, and translate natural-language project requirements into validated command arguments without executing the CLI.

Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.

Enables AI clients to call the documented APIs of real business platforms—job boards, freelance marketplaces, ad networks, e-commerce, messaging, social, sales, trading and market data—through a single CLI and runtime. Serves 455 catalogued platforms with one shared verb vocabulary per category, in both Python and TypeScript.

An MCP server with LangGraph agent integration that enables AI agents to use custom tools and external APIs for dice rolling, web search, social content creation, and GitHub access via STDIO transport.

Exposes a support-desk application through MCP tools and resources with populate/snapshot/restore hooks for reproducible RL training episodes.

Facilitates spec-driven development workflows by providing structured prompts for generating requirements in EARS format, design documents, and implementation code following a systematic approach.

A proxy server that allows LLM clients to use Databutton app API endpoints as tools through the MCP protocol over websockets.

Generates compiled Flutter apps from JSON Product Requirements Documents. Exposes endpoints for PRD validation, schema, payment terms, and build status.