"How to Interact with Firebase Projects" matching MCP servers:

An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.

Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.

MCP server that translates natural-language questions into SQL, validates every query structurally, and executes approved read-only queries against a SQLite database, returning results and rejections.

Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.

Enables users to interact with PostgreSQL databases through natural language, with GitHub OAuth authentication and role-based access control.

A secure database query service built on FastMCP framework that allows users to query MySQL databases using natural language, with comprehensive permission management and security controls.

An MCP server for integrating with the Brave Search API, and it supports HTTP proxying.

Searches Reddit for answers to questions and saves Q&A sessions to Notion.

A Model Context Protocol server that enhances LLM capabilities by connecting to Wikipedia, internet search (Tavily), and financial data (Yahoo Finance) tools, enabling contextual responses to user queries.

Transforms SAP S/4HANA or ECC systems into conversational AI interfaces by exposing all OData services as dynamic MCP tools. Enables natural language interactions with ERP data including querying, creating, updating, and deleting entities through SAP BTP integration.

Custom MCP server for NotebookLM that adds audio source upload, YouTube source ingestion, source readiness polling, and transcript export, complementing standard Q&A and audio overview tools.

A lightweight RAG system that provides an MCP server for searching and interacting with vector-based knowledge bases. It enables users to perform retrieval-augmented generation and search across Qdrant collections through a standardized interface.

A semantic layer query engine with MCP support, enabling AI assistants to query structured data through natural language and declarative interfaces.

Enables querying SINTEGRA TO (state tax information) through a read-only MCP server, using natural language.

Shelfmark is an MCP server that builds a local metadata catalogue of your documents, enabling AI agents to discover, search, and select relevant files without opening or indexing their contents. It provides governed access with ownership and confidentiality controls, ensuring agents only see what they are permitted to.

An MCP server that exposes real-time financial data tools for stock search, company info, historical prices, and financial metrics from Yahoo Finance, enabling AI agents to answer natural-language questions about stocks and financial markets.

Enables AI models to manage a Drupal-shaped content store over MCP, including nodes, vocabularies, terms, tag filtering, and trigram/semantic search, while logging every tool call for observability.