"Proof-of-Concept Examples for Multi-Component Processes (Model Context Protocol)" matching MCP servers:

MCP server enabling real-time weather queries via Tavily API and internet usage data by country via MongoDB.

MCP server for exploring and querying Supabase databases with interactive React widgets for schema browsing, table viewing, and SQL execution.

A secure multi-tenant server that provides real-time context to LLMs via REST API, using JWT authentication and PostgreSQL row-level security for tenant isolation.

A middleware server that intelligently routes AI model queries to appropriate data sources, providing contextual information to enhance AI responses.

Allows AI assistants to interact with Square's connect API, providing access to Square's complete API ecosystem for managing payments, orders, customers, inventory, and more.

A Model Context Protocol server that enables LLMs to interact directly with MongoDB databases, allowing users to query collections, inspect schemas, and manage data through natural language.

A server that allows AI models to interact with PostgreSQL databases through a standardized protocol, providing database schema information and SQL query execution capabilities.

ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.

A multi-purpose MCP server for AI-powered healthcare assistance that processes clinical data through configurable LLM providers. Maintains webhook endpoints for patient data processing with PostgreSQL logging and OpenAPI documentation.

A comprehensive production-ready MCP server with AI integration, plugin management, and web-based administration. Features multi-database support, RAG capabilities, SSH/SFTP access, and a built-in plugin hub for managing the MCP ecosystem.

Enables agents to query governed metrics through MCP, including describing metrics, running deterministic SQL against a warehouse, explaining join path preferences, and searching semantically ambiguous terms.

MCP server providing deep PostgreSQL context to AI assistants, including schema DDL, index health, foreign key associations, query execution plans, and performance statistics via read-only tools.

Read-only MCP server for querying PostgreSQL, MySQL, and SQLite from AI agents — multi-database, safe by default.

A knowledge graph memory server using SQLite to provide persistent, isolated contexts for organizing information into searchable categories like work and personal projects. It features unique ID-based operations and a token-efficient serialization format designed to optimize interactions with LLMs.

Enables agents to query a local macOS archive of Knowledge and browser history through read-only stdio MCP tools for status, timelines, search, original records/blobs, schemas, bounded SQL, and usage or domain summaries.

A Model Context Protocol server that provides read-only access to PostgreSQL databases with enhanced multi-schema support, allowing LLMs to inspect database schemas across multiple namespaces and execute read-only queries while maintaining schema isolation.

Enables read-only SQL queries across several named MySQL/MariaDB/Aurora and Postgres databases from one place, with tools to list databases, tables, and describe schemas. It enforces safety by requiring non-local hosts to be read replicas and by running every statement in a rolled-back read-only transaction.

MCP server for connecting to Microsoft Fabric and Power BI semantic models, enabling workspace browsing, dataset management, TMSL retrieval, DAX queries, model creation/editing, and includes a Best Practice Analyzer with 71 rules.

Provides AI assistants with read-only access to inspect database schemas, preview data, and run safe queries across PostgreSQL, MySQL, MongoDB, and SQL Server. It enables AI tools to understand database structures and relationships automatically to generate more accurate code.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.