Self-hosted knowledge manager and MCP server that lets you organize snippets, questions, and documents via a web UI and exposes them to AI assistants for reading and writing.
A simple Model Context Protocol (MCP) server with ChromaDB integration, allowing AI assistants to interact with ChromaDB for vector storage and retrieval operations.
A template project for building custom MCP servers that enables direct access to PostgreSQL databases, allowing SQL query execution and schema information retrieval through the Model Context Protocol.
An MCP server that extends AI agents' context window by providing tools to store, retrieve, and search memories, allowing agents to maintain history and context across long interactions.
Enables LLMs to store, search, and manage memories with hybrid semantic and keyword search using ChromaDB and Neo4j for persistent memory and knowledge graph capabilities.
A simple application demonstrating Model Context Protocol (MCP) integration with FastAPI and Streamlit, allowing users to interact with LLMs through a clean interface.
The Flowise MCP Server enables clients to list chatflows and call predictions, integrating seamlessly with DIY Flowise or Flowise Cloud accounts. It provides a simple interface for executing chatflows/assistants predictions with existing Flowise configurations.
Connect your Sanity content to AI agents. Create, update, and explore structured content using Claude, Cursor, and VS Code via the Model Context Protocol. Transform content operations from complex queries to simple conversations—giving your team superpowers without sacrificing structure.
Enables natural language interaction with MySQL Sakila database through intent-based tools for movie search, customer management, rental operations, and business analytics without exposing database schema.
A local MCP server that allows AI systems to search and retrieve information from a custom knowledge base generated from markdown files. It provides tools for natural language text search, category browsing, and specific content chunk retrieval.
A demonstration project for Model Context Protocol (MCP) that integrates weather services with multiple AI models (Claude, GPT, Gemini), enabling natural language queries for weather alerts and forecasts.
A simple AI development tool that helps users interact with AI through natural language commands, offering 29 tools across thinking, memory, browser, code quality, planning, and time management capabilities.