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Showing 313–336 of 2,434 for Pydantic AI and Box MCP

Memory Store MCP Server

A Model Context Protocol (MCP) server that provides web search capabilities using Puppeteer, returning structured JSON results. It is designed for easy…

Notion MCP Server

# Notion MCP Server A Model Context Protocol server for Notion integration, allowing Claude and other LLMs to interact with your Notion workspace. ## Features…

Notion MCP Server

A Model Context Protocol server for Notion integration that allows Claude and other LLMs to interact with a Notion workspace through tools like search, page…

Solon Ai

Java AI application development framework (supports LLM-tool,skill; RAG; MCP; Agent-ReAct,Team-Agent). Compatible with java8 ~ java25. It can also be embedded…

CostAffective-MCP

Intelligent repository context for AI coding assistants. Provides code search, symbol lookup, call graphs, and reference tracking via MCP. Uniquely designed to…

Rag Starter

# rag-starter — chat with your documents (RAG), with citations A production-ready starter that turns a folder of documents into a **cited Q&A service**. Drop…

W3c Mcp Server

MCP Server for accessing W3C/WHATWG/IETF web specifications. Provides AI assistants with access to official web standards data including specifications, WebIDL…

Simple Memory

An MCP server to extend the context of agents. Useful when coding big features or vibe coding and need to store/recall progress, key moments or changes or…

Tela

Self-hostable, markdown-native team wiki with a built-in MCP server: agents search, read, and write your wiki pages (ranked Postgres full-text + semantic…

Memory Cache Server

Memory Cache Server is a Model Context Protocol (MCP) server that reduces token consumption by automatically caching data between language model interactions…

Sequential Thinking

Sequential Thinking is an MCP server that provides a tool for dynamic and reflective problem-solving through a structured, step-by-step thinking process. It is…

RagWiser

RagWiser is a Retrieval Augmented Generation (RAG) system built with Spring Boot that enables users to upload PDF documents, process them, and ask questions…