Model Context Protocol (MCP) server implementation for semantic search and memory management using TxtAI. This server provides a robust API for storing, retrieving, and managing text-based memories with semantic search capabilities. You can use Claude and Cline AI Also
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
A lightweight, zero-config MCP server that makes documentation and API specifications instantly accessible to AI models using the llms.txt standard. It enables searching and retrieving full documentation, OpenAPI, and AsyncAPI specs without requiring a complex RAG infrastructure or vector database.
An MCP server for API discovery and execution with a token-efficient search -> execute workflow over OpenAPI, Google Discovery, and optional native GraphQL and gRPC sources.
A lightweight MCP server that enables intelligent tool management and semantic search for APIs using sentence-transformers. It supports both REST and MCP interfaces across dual transport modes, allowing users to upload, manage, and query API tools with natural language.
MCP server that enables agents to dynamically switch between multiple AI models (OpenAI, Anthropic, Google, etc.) with unified protocol-driven configuration and capability discovery.
