"Connecting Firebase to a data source or application" matching MCP servers:

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

Multi-datasource MCP server that connects AI assistants to 6 database types (MySQL, PostgreSQL, ClickHouse, MongoDB, SQLite, Huawei DWS) with dynamic configuration, encrypted credential storage, and schema discovery.

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

Enables AI assistants to work directly with Firebase realtime database

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

Exposes Firebase emulator data (Firestore, Auth, Realtime Database, and logs) to AI coding assistants for local development inspection.

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.

Analyzes source code dependencies across multiple programming languages in the specified directory to identify file relationships, assisting in dependency management and project structure understanding.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

An MCP server that enables AI assistants to navigate, search, and analyze local Keycloak source code to support developer customizations like SPIs and authenticators. It provides tools for searching classes, generating boilerplate code, detecting breaking changes between versions, and tracing dependencies.

Indexes Unreal Engine source code into a local database, providing AI coding assistants with deep structural queries like class hierarchies, call graphs, and full-text search across all engine source files.

Provides AI tools with on-demand, precise access to real AOSP framework and AndroidX source code, so they can search classes, extract exact method bodies with Javadoc, inspect inheritance hierarchies, and trace definitions and references across the entire tree. Sources are synced locally for fast, offline lookups, with optional language-server features for cross-file navigation.

An MCP Server that provides natural language access to Google's Firebase Realtime Database API, enabling database operations and management through conversation.

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.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

A Model Context Protocol server that extracts embedded data (such as i18n translations or key/value configurations) from TypeScript/JavaScript source code into structured JSON configuration files.

Enables converting a public release-note URL into ordered upgrade tasks with source excerpts, anchors, confidence, and uncertainty, without executing release text or project code.

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

Enables mapping JavaScript error stack traces back to original source code, extracting context information to help developers locate and fix issues.

Routes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.