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A template for deploying MCP servers on Vercel with serverless functions. Includes example tools for rolling dice and getting weather data to demonstrate basic functionality and API integration patterns.

Enables users to manage medical appointments by searching for doctors, checking availability, and booking sessions through a natural language interface. It serves as a reference implementation for advanced MCP features like symptom-based specialist recommendations and multi-step scheduling workflows.

Meelion MCP ) connects AI assistants and automated clients to Meelion's structured data: a Brazilian platform for researching, comparing, and tracking investments, focusing on fixed income, indicators (Selic, CDI, IPCA, savings) and exchange rates (dollar, euro, gold, silver, Bitcoin).

A simple note storage system that allows creating, storing, and summarizing notes with customizable detail levels.

A robust server for managing long-term agent memory using Mem0, providing efficient storage and retrieval of agent memories with a lightweight Python-based implementation.

Provides AI coding assistants with persistent memory storage using a local SQLite database. Enables tools to remember project details, notes, and relationships across sessions to maintain context and reduce repetitive explanations.

Enables AI assistants to store and retrieve memories with semantic search capabilities using vector embeddings. Provides persistent memory storage with SQLite backend for context retention across conversations.

MCP Memory Bank (mcp-memory-bank-6fa32141)

A powerful, production-ready context management system for Large Language Models (LLMs). Built with ChromaDB and modern embedding technologies, it provides persistent, project-specific memory capabilities that enhance your AI's understanding and response quality.

Enables AI assistants to remember user information across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage and retrieval.

🧠 High-performance persistent memory system for Model Context Protocol (MCP) powered by libSQL. Features vector search, semantic knowledge storage, and efficient relationship management - perfect for AI agents and knowledge graph applications.

Enables AI assistants to store and retrieve long-term memories using PostgreSQL with vector similarity search. Supports semantic memory operations, tagging, and real-time updates for persistent learning across conversations.

A persistent local vector memory server that allows users to store and search project-specific context using LanceDB and local embeddings. It enables MCP-compliant editors to maintain long-term memory across different projects without requiring external API keys.

Provides persistent memory functionality for AI conversations by creating, managing and querying entities and relationships in a knowledge graph. Features SQLite storage, advanced search capabilities, and Windows auto-start integration for long-term AI memory retention.

Provides intelligent memory management capabilities using Qdrant vector database for semantic search and storage. Supports global, learned, and agent-specific memory types with markdown processing and duplicate detection.

A cloud-based vector memory service that provides AI assistants with persistent storage, semantic search, and entity management via the Model Context Protocol. It features multi-tenant isolation and bidirectional synchronization with macOS and Google contacts and calendars.

Enables persistent storage and retrieval of decisions, settings, and operational rules across chat sessions, maintaining context continuity and decision consistency for long-term development projects through structured memory management.

MCP Mianshiya Server

MCP Server面试鸭搜索题目的服务

A tutorial implementation MCP server that enables analysis of CSV and Parquet files. Allows users to summarize data and query file information through natural language interactions.

Enables AI agents to query and introspect MongoDB databases through find, aggregate, and schema discovery operations. Supports read-only default mode with optional write capabilities and works with any MCP-compatible client via stdio or HTTP transports.

A Model Context Protocol server that allows Large Language Models like Claude to execute SQL queries, explore database schemas, and maintain persistent connections to SQL Server databases.