GenAIScript is a JavaScript runtime dedicated to build relaible, automatable LLM scripts. Every GenAIScript can be exposed as a MCP server automatically.
Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.
An MCP server implementation that maximizes Gemini's 2M token context window with tools for efficient context management and caching across multiple AI client applications.
An MCP server that connects to Tana's Input API, allowing Large Language Models and other MCP clients to create and manipulate data in Tana workspaces.
A Model Context Protocol server that enables Claude and other LLMs to interact with Notion workspaces, providing capabilities like searching, retrieving, creating and updating pages, as well as managing databases.
A tool that helps easily register Anthropic's Model Context Protocol (MCP) in Claude Desktop and Cursor, providing RAG functionality, Dify integration, and web search capabilities.
An MCP server that enables LLMs to understand and work with TypeScript APIs they haven't been trained on by providing structured access to TypeScript type definitions and documentation.
An MCP server aimed to be portable, local, easy and convenient to support semantic/graph based retrieval of txtai "all in one" embeddings database. Any txtai embeddings db in tar.gz form can be loaded
Provides AI-powered assistance for coding problems using Google's Gemini AI, combined with Perplexity insights and Stack Overflow references, facilitating contextual analysis and automatic response archiving for improved troubleshooting.
A TypeScript implementation of a Model Context Protocol server that provides a frictionless framework for developers to build and deploy AI tools and prompts, focusing on developer experience with zero boilerplate and automatic tool registration.
A Model Context Protocol server that connects Claude and other AI assistants to your Notion workspace, allowing AIs to interact with databases, pages, and blocks.
An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context
A Machine Control Protocol (MCP) server that enables storing and retrieving information from a Qdrant vector database with semantic search capabilities.
A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.
Enables storage and retrieval of knowledge in a graph database format, allowing users to create, update, search, and delete entities and relationships in a Neo4j-powered knowledge graph through natural language.