"A platform for competitor analysis in QR-based restaurant management systems" matching MCP servers:

MCP server exposing restaurant tools including search by cuisine, price, rating, and open status, restaurant details, user preferences stored in Neon Postgres, and RAG knowledge search covering 50 mock restaurants across Scottsdale and Phoenix.

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-powered access to authoritative design systems knowledge, including W3C standards, WCAG guidelines, and best practices from 188+ curated entries via semantic vector search.

Enables MCP-based access to Adhoc documentation, providing search, content retrieval, and feedback issue creation with audience gating and leak protection.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

MCP server for integrating manufacturing systems (MES/ERP/quality/maintenance) with LLM agents, enabling event ingestion, incident triage, approval workflows, and RAG-based knowledge retrieval.

Enables MCP hosts like Cursor or Claude to query an enterprise knowledge base via stdio, providing RAG-based answers with cited sources.

Enables enterprise knowledge search through a chat interface, comparing traditional RAG with MCP-driven retrieval using hybrid BM25 and dense vector search, Ollama-powered answer generation, and question routing to domain-specific retrieval tools.

MCP server that parses aviation accident reports (PDF/DOCX/TXT) and injects their content into extraction prompt templates for knowledge graph construction.

Enables AI agents to answer Power Platform governance questions — data policies, connectors, environments, Managed Environments, security roles, the CoE Starter Kit and ALM — using hybrid keyword-plus-semantic search over Microsoft's documentation, with a deep link to the exact section behind every answer. It runs locally without API keys, offers read-only search, section-reading and document-listing tools, and connects to Claude, VS Code and Copilot Studio.

Enables AI assistants to directly access quant research knowledge, including factor libraries, strategy backtesting, and research reports, through the MCP protocol.

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...

Enables support engineers to analyze tickets against a help center with cited retrieval, role-gated and human-confirmed actions, and safety-gated evaluation.

Enables retrieval-augmented question answering with source-grounded citations, document retrieval, and idempotent ingestion through MCP tools.

Enables AI coding assistants to query private academic paper collections via standard MCP tools, with hybrid retrieval, reranking, and inline citations.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

提供文档智能问答的MCP服务器，支持查询知识库、获取会话历史和清理会话历史。

Enables governed, read-only SQL analytics, hybrid RAG knowledge search, financial metric calculation, and database schema introspection through MCP, with role-based access control, audit logging, and AI observability.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

AI-powered agentic workspace by Ambuj Systems for career intelligence, resume tailoring, and claim verification.

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.

Enables agents to optimize context-window attention by reordering retrieved documents so critical evidence lands at prompt boundaries, mitigating lost-in-the-middle degradation. It combines BM25 lexical scoring, dense vector similarity, reciprocal rank fusion, knowledge-graph expansion, and recency-decay memory caching, exposed as a zero-dependency MCP stdio server.

A proof of concept MCP server for Apache OFBiz

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Jira Service Management (beta): https://www.cdata.com/download/download.aspx?sku=GKZK-V&type=beta

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 agents to run hybrid retrieval, reciprocal rank fusion, knowledge graph expansion, semantic caching, and context reordering so critical evidence is placed at prompt boundaries to reduce lost-in-the-middle degradation.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

WordPress plugin that runs an MCP server on your own site: search and read published posts and pages, look up WooCommerce products, describe the site as schema.org types and query site figures, with drafts only when the site enables them. Signed-in access by default; anonymous access and OAuth are optional and off.

A reusable runtime infrastructure for hosting Model Context Protocol servers and tool registries over HTTP. It provides built-in validation, authentication, and logging to simplify the deployment of AI-powered workflows.

A development platform that helps AI developers optimize prompts through intelligent context management, providing tools for analysis, optimization, and template management to reduce costs and improve AI response quality.