"Model Context Protocol (MCP) Servers Repository" 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 server that allows AI models to interact with PostgreSQL databases through a standardized protocol, providing database schema information and SQL query execution capabilities.

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 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.

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.

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.

Enables cross-window context sharing in VS Code by persisting Copilot conversations to SQLite, allowing code discussions from one repository to be accessible in other VS Code windows through smart entity matching and search.

MCP server for reading and analyzing Fabric semantic models. Supports getting model definitions and executing DAX queries against Power BI datasets.

An MCP server that gives models semantic context about a data warehouse, including table meaning, units, lineage, and health, to reduce guessing.

Indexes codebases into a SQLite database to provide metadata, exports, dependency graphs, and change tracking for JS/TS projects. It enables users to search for symbols, map internal dependencies, and monitor file changes through MCP tools and a web dashboard.

Enables agents to pull compact MySQL row diffs into their context, supporting before/after changes via triggers or watermark-based updates, with tools to fetch and acknowledge changes.

A memory management system that enables AI assistants to store, search, and visualize persistent conversation contexts using a Neo4j graph database. It provides an MCP server for integration with Claude Desktop along with a web-based dashboard for managing relationship-based knowledge.

A powerful MCP server that extracts, stores, searches, and analyzes Claude.ai conversations with SQLite database, semantic search, and multiple export formats including Obsidian and PDF.

CTX is a tool made to solve a big problem when chatting with LLMs like ChatGPT or Claude: giving them enough context about your project.

Enables AI agents to inspect supported databases read-only, export sanitized DDL and metadata plus bounded masked samples into organized context, and run approved procedure or function updates through a shared local service.

Enables MCP clients to search encrypted, self-hosted archives and retrieve bounded records from Apple, Canvas, Health, travel, and Obsidian sources while checking sync freshness.

Enables AI systems to securely query databases using structured intents (MDBP) with automatic schema discovery and policy enforcement.

An MCP server that provides an interface for querying the AtherOS knowledge base through an API, allowing users to create chat sessions and send queries to retrieve information.

Builds rich code graphs from TypeScript/NestJS codebases using AST analysis and Neo4j, enabling semantic search, natural language querying, and intelligent graph traversal to provide deep contextual understanding of code relationships and dependencies.

Enables AI agents to safely inspect a PortalV4 project's real structure, database schema, and Git status, while enforcing backend architecture rules, automating API documentation, and generating test templates without modifying repositories.

An MCP server that exposes personal financial data — transaction ledger, portfolio holdings, live/historical market prices, and quantitative risk metrics — as standardized tools, resources, and prompts, enabling natural language reasoning over real computed numbers.

Converts Excel table definitions to structured JSON and exposes them to LLMs via MCP tools like list_tables and get_table_schema, enabling accurate SQL generation and data modeling assistance.