"A platform for collaboration and communication - Feishu" matching MCP servers:

Provides access to Feishu (Lark) documents for AI-driven coding tools like Cursor, Windsurf, and Cline based on Model Context Protocol implementation.

Enables collaboration with multiple AI providers (Claude, GPT-4, Gemini, Ollama) directly from VS Code with automatic project context injection and persistent conversation history. Provides streamlined tools for getting AI advice, multi-provider research, and enhanced context sharing across sessions.

Enables AI agents to use Feishu (Lark) spreadsheets as long-term memory and personal knowledge base with retrieval-augmented generation (RAG) via the Model Context Protocol.

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

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 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.

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

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.

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 MCP server that enables multi-provider AI collaboration using models like DeepSeek, OpenAI, and Anthropic through strategies such as parallel execution and consensus building. It provides specialized tools for side-by-side content comparison, quality review, and iterative refinement across different AI providers.

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 proof of concept MCP server for Apache OFBiz

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

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.

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

Enables AI assistants to retrieve, search, and compare procurement documents using hybrid retrieval and MCP integration.

High-performance Model Context Protocol server supporting multiple LLM providers (OpenRouter, OpenAI, Groq) with WebSocket API and conversation history persistence.

Provides AI assistants with real-time web search, reasoning, and research capabilities through Perplexity's Agent API and Search API, enabling tools for search, conversational Q&A, deep research, and advanced reasoning.

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.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

Enables governed, audit-traced AI access to a curated knowledge base through the Model Context Protocol, with OAuth 2.1 authentication and policy enforcement for secure, compliant queries.

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

Read-only MCP server for NEURA's AI news platform, enabling clients to list, search, and retrieve published articles in English and Italian.

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.

A powerful AI service platform that provides complete MCP tool calling capabilities and RAG knowledge base functionality, enabling users to connect to multiple MCP servers and perform intelligent document search.