"A simple test or quiz" matching MCP servers:

Simple, fast, long-term memory for your AI chatbots, agents, and MCP tools. Give your LLM a persistent memory using a local SQLite file. No complex database servers, no heavy cloud setup, and zero C++ compilation errors. Works everywhere.

Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

A persistent, project-scoped memory layer for AI agents, supporting hybrid retrieval (vector, keyword, and tag matching) and sharing across different MCP clients like Claude Code, Qoder, or Cursor.

Enables Codex, ChatGPT, and Aside to share project work memory by reading private GitHub-backed checkpoints and searching or re-reading allowed local/SSD documents through read-only MCP tools.

Provides AI-powered search and documentation tools using Google Vertex AI or Gemini API with real-time web search grounding, enabling technical queries, code analysis, documentation retrieval, and architecture recommendations to overcome LLM knowledge gaps.

A Model Context Protocol server that enables AI assistants to analyze images using OpenRouter vision models through a simple interface.

Provides a compiled knowledge substrate, extracting atomic claims from an append-only capture log and querying a bitemporal claim graph over MCP. Read-only by default, with opt-in writes for trusted sources.

Exposes course documents as searchable resources and provides tools for reading, study task management, and source-grounded quiz prompts. Supports hybrid retrieval and integration with DeepSeek-based agents.

Enables AI coding agents to intelligently index and search codebases with sub-20ms retrieval, 8x memory compression, and cross-encoder reranking via MCP stdio.

A local MCP server that indexes files in a directory using Gemini Embedding 2, enabling AI agents to perform semantic search over local documents.

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.

Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.

This server allows users to perform web searches using Perplexity AI, providing a tool for retrieving search results through a simple API interface.

Enables AI assistants to intelligently select and switch between different AI models (OpenAI, Anthropic, etc.) within the same conversation based on task requirements. Provides a unified interface for accessing multiple AI providers through a single MCP tool.

An MCP server that enables AI models to retrieve information from Ragie's knowledge base through a simple 'retrieve' tool.

Enables natural-language Q&A over multi-source documents (PDF/Markdown/web) with a self-reflective retrieval-augmented agent that cites sources, retries on poor retrieval or grounding, and supports multi-turn memory.

A Claude integration tool that enables users to query and analyze Aliyun (Alibaba Cloud) Simple Log Service logs through natural language commands.

A Model Context Protocol server that runs on Cloudflare Workers with OAuth login, allowing clients like Claude Desktop to connect to it for tool-augmented AI interactions.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

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.

A simple MCP server that implements a note storage system with RAG capabilities, allowing users to store notes and generate summaries of stored content.

A utility tool that enables Claude Desktop to interact with external tools via the Model Context Protocol, providing features like email sending and simple calculations while simplifying the MCP setup process.

Enables AI agents to persist, search, and evolve knowledge through a Markdown vault with a typed knowledge graph and MCP interface.

Pre-trade risk validation and position sizing for AI trading agents via G-formula and Iron Fist.

缔零法则MCP是基于LLM和RAG技术搭建的实现完全替代人力的全自动化风险识别的内容安全审查平台，致力于通过代理AI技术减少人力成本，高效高精度为用户提供分钟级接入的内容风控解决方案，破解安全威胁，提供从风险感知到主动拦截策略执行的全链路闭环与一体化解决方案。This MCP tool is an AI-powered content security review platform built on LLM and RAG technologies, designed to achieve fully automated risk identification that completel

A proof of concept MCP server for Apache OFBiz

MCP server for Vectros, a typed multi-tenant record store with hybrid search and citation-grounded RAG, enabling agents to query, search, and ask questions over their own indexed data.

Provides AI coding agents with persistent memory by recording sessions and normalizing them into a searchable knowledge graph, then delivering relevant context at the start of the next session.

MCP server that provides secure access to a serverless Markdown wiki on AWS, enabling AI assistants to read, search, and edit pages with space-level permission checks and Bedrock-powered semantic search.

Enables source-first orchestration and knowledge indexing with inspectable architectural capabilities through a unified MCP interface, including named-attribute retrieval and atomic knowledge ingestion.

Search a folder of documents and check answers against them. Offline: no API key or database.

A Model Context Protocol server that enables Claude to collaborate with Google's Gemini AI models, providing tools for question answering, code review, brainstorming, test generation, and explanations.

Enables programming agents to retrieve internal R&D documentation with traceable, reproducible evidence through the MCP protocol, supporting multi-corpus routing and access control.

Enables searching imported AI conversations locally across different providers from an MCP client, with read-only access to the archive.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

he Maximo MCP Server bridges AI agents (Claude, Cursor, Antigravity) with your IBM Maximo environment. It empowers your AI to autonomously discover Object Structures (APIs), inspect schemas, and query live data via OSLC. Instead of hallucinating field names, the AI validates queries instantly and ca