"Firebase: Google's Backend-as-a-Service Platform" matching MCP servers:

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables AI agents to manage VPN infrastructure through provisioning, lifecycle control, traffic routing, and health monitoring.

An MCP Server providing access to Google's Firebase API, allowing natural language interaction with Firebase services and resources.

A Django app that implements Firebase Model Context Protocol server, enabling AI agents to interact with Firebase services (Authentication, Firestore Database, Cloud Storage) through a standardized protocol.

Provides a SQLite-backed MCP server that records agent memory as history, enabling explicit consolidation, source checks, revisions, narrative versions, and accountable forgetting.

A template for building MCP backends for lab equipment with an embedded Echo example for immediate testing and development.

A Docker-based local RAG backend that provides advanced document search capabilities using vector, graph, and full-text retrieval via the Model Context Protocol. It supports over 28 file formats and tracks evolving relationships between concepts using a Neo4j-backed graphiti implementation.

MCP server that exposes an email verification tool, returning verdicts of valid, invalid, or risky with reasons.

Enables managing personal expenses through MCP tools for registering and listing gastos, reusing the backend's service layer.

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.

An MCP server that enables interaction with the Firebase App Check API, allowing users to verify and manage the authenticity of requests to Firebase backend services through natural language.

Exposes the shared health-check service as an MCP tool, letting clients query status, uptime, and version through the streamable HTTP endpoint.

Enables structured dynamic analysis of authorized Windows processes via Cheat Engine 7.7, exposing bounded tools for process inspection and debugging without arbitrary code execution or memory writes.

An MCP server that provides a conversational interface to Firebase Rules API, allowing users to manage and deploy rules that determine data access in Firebase services.

Enables AI agents to interact with Firebase services including Authentication, Firestore Database, and Cloud Storage through a standardized MCP protocol.

Exposes workspace-scoped Backend project queries via MCP, enabling explicit token pairing, status checks, and scoped sync of project docs, source artifacts, graph data, and evidence metadata without background synchronization.

Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.

Deterministic SNAP eligibility logic, exposed as auditable Model Context Protocol tools. An AI agent can read, reason, and orchestrate, but the eligibility determination itself is made by versioned, tested, cited code that a caseworker, an auditor, or a court can inspect.

Lets an AI assistant read and write business records in plain language, including looking up people, creating and updating tasks, logging time, and pulling utilization reports through a synthetic ops platform or an optional ClickUp adapter.