"F#" matching MCP servers:

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.

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

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

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

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.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

Enables secure read-only access to Tencent Lexiang knowledge bases via MCP, including listing directories, RAG search, and reading entries.

Enables AI clients to explore MCP concepts, retrieve quickstart guides, and ask questions with Redis-cached answers, supporting deployment on Cloudflare Workers and Docker.

Enables users to access real estate property industry news daily and search a specialized knowledge base covering laws, regulations, company info, and more.

Enables querying of live organizational data (student records, outcomes, certifications, finances, donations, communications) via Claude using structured database queries and semantic search.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Enables AI agents to provide e-commerce customer service with product search, RAG-based FAQ answers, human handoff, and automated security auditing with a review workflow.

Provides clean, bounded web content to AI by filtering HTML noise and optionally summarizing, preventing context window overflow.

Provides MCP tools to search, retrieve, and answer questions from the public Open Finance Brasil Confluence documentation using BM25-based local indexing.

Provides tools for searching Agent8 game development code examples and system prompts to assist in Agent8 SDK development.

CodebaseAgent-MCP is an MCP server that uses a lightweight RAG pipeline to delegate repository analysis to a dedicated OpenAI-compatible LLM, reducing token consumption by having the primary assistant receive only the relevant findings instead of repeatedly scanning the entire codebase.

Enables AI agents to write, validate, and render high-quality PostScript by providing operator lookup, vetted PSlib fragments, cited reference search, and Ghostscript-based checking.

Hermetic memory for AI agents — one Rust binary, one SQLite file, zero network. Recall returns evidence with provenance or abstains: no code path for making things up.

An MCP server that provides persistent memory capabilities for AI agents using Mem0, enabling storage, search, and management of contextual information across conversations with support for multiple backends and LLM providers.

Provides e-commerce customer support tools for order status, delivery, account, and policy questions, with RAG-grounded retrieval and strict authorization checks over mock data.