What is an MCP server?
An MCP server is a program built on the Model Context Protocol that wraps a tool, data source, or API — like file access, a database, or web search — into a capability an AI assistant can discover and call.
Discover awesome MCP servers.
garyedgington
Text Summarizer condenses long-form content into structured, actionable summaries so AI agents and applications can work with information faster and at lower cost. Feed it meeting notes, research articles, documentation, JSON payloads, or Markdown files and get back a clean summa
rocnubie
Flow Music AI (flowmusicai.app) is a browser-based AI song generator that converts a plain-text description into a fully produced, mixed track in roughly 80 seconds. You type a one-line brief, optionally choose genre tags and a vocal mode, paste your own lyrics or let the built-i
Octid-io
Agentic AI instruction encoding. 86.8% smaller than JSON. Inference-free decode by table lookup. 342 opcodes, 26 namespaces, three conformant SDKs. Confirmed over LoRa mesh radio. Apache 2.0 with express patent grant.
swisstruthorg
Verified knowledge base for AI agents via MCP — certified facts with source references, confidence scores, and SHA256 integrity hashes
Yuchen20
🧠 𝑴𝒆𝒎𝒐𝒓𝒚-𝑷𝒍𝒖𝒔 is a lightweight, local RAG memory store for MCP agents. Easily record, retrieve, update, delete, and visualize persistent "memories" across sessions—perfect for developers working with multiple AI coders (like Windsurf, Cursor, or Copilot) or anyone who
thlg057
MCP server that gives AI coding agents instant access to Thomson MO5 technical documentation via semantic search.
askme765cs
Recon-Fuzz
Search Recon documentation, book, and newsletter. Queries getrecon.xyz, book.getrecon.xyz, and getrecon.substack.com for fuzzing, invariant testing, and Chimera framework knowledge.
grainne-b
pomazanbohdan
A high-performance, pure Rust Model Context Protocol (MCP) server that provides persistent, semantic, and graph-based memory for AI agents.
itsiiromiuy
ogham-mcp
Persistent shared memory for AI agents. Hybrid search (pgvector + tsvector), knowledge graph, cognitive scoring, and 16-language temporal extraction. 97.2% Recall@10 on LongMemEval with one PostgreSQL query. Works across Claude Code, Cursor, Codex, OpenClaw, and any MCP client
crman
laptou
kaaustubh
usememra
Memra MCP server — persistent memory for AI agents. EU-hosted, privacy-first, sub-100ms hybrid recall.
ayvazyan10
Persistent AI memory backend with semantic search and knowledge graph.
PaymanAI
MCP server, providing AI with access to the payman documentation
LaserFocused-ee
MCP server for providing documentation to Claude
CodeAlive-AI
Provides a bridge to CodeAlive's platform for semantic code search, repository exploration, and context-aware chat completions that leverage deep understanding of entire codebases including documentation and dependencies.
0ics-srls
Semantic code knowledge for your stack. Hosted MCP over 800+ pre-indexed OSS libraries (C#, Java, TS, Python, Rust, PHP+). 17 SCIP-backed tools for real source, callers, usages, tests, and hierarchies — one call each, free.
amanasmuei
The memory layer for AI coding tools. Local-first, semantic, 9 MCP tools with consolidation and project scoping. Works with Claude Code, Cursor, Windsurf & any MCP client.
brianxiadong
A Spring AI MCP-based service for retrieving ONES Wiki content and converting it to AI-friendly text format.
scitara-cto
seritalien
Verifiable Memory-as-a-Service for AI agents. Persistent, searchable, graph-connected knowledge with optional Starknet
phoenine
A simple MCP server that integrates with Notion's API to manage my personal habit track.
crosmos-labs
Persistent memory for AI agents. Give your coding assistant organizational context that compounds — search memories with hybrid retrieval, store anything with auto entity extraction, and query a living knowledge graph that gets smarter over time.
supermaxlol
Cognitive memory system for AI agents with 129 MCP tools. Persistent hierarchical memory, emotional recall, knowledge graphs, spreading activation, hybrid retrieval (BM25+RRF), metacognition, goal tracking, spaced repetition, dream consolidation, and more.
rickydata-indexer
sgx-labs
Memory with integrity for AI coding agents. SAME tracks provenance, flags stale knowledge, and surfaces contradictions; so your AI trusts what's current, not what's outdated.
alfredoizdev
Persistent memory MCP server for Claude. Store decisions, code snippets, and knowledge that
ConvergentMethods
Compile semantic document edits into correct Google Docs batchUpdate requests. UTF-16 arithmetic, cascading index shifts, OT-compatible ordering. MIT licensed.
crossagent
helper for build a mcp server
Shivansh12t
tlemmons
A shared memory and coordination server for multiple AI coding agents, built on the Model Context Protocol
attilakiss9000
Preserves the emotional texture of human-AI conversations across sessions through real-time experiential annotation — temperature, authenticity, shifts, subtext, and unspoken context.
RahulSaini02
This repo is dedicated to learning and working with large language models (LLMs), prompt engineering, and modern GenAI tools such as LangChain, RAG, and vector databases.
apifyforge
Autopoietic knowledge synthesis gives AI agents access to 18 academic and technical data sources unified by a suite of advanced mathematical frameworks — stochastic block model community detection, Turing instability, Smith normal form Betti numbers, formal concept analysis, Fish
vikramdse
Library docs MCP server
LostInBrittany
This MCP demo Server based on FastMCP, exposes Clever Cloud's Documentation
chiisen
使用 Hexo 架設簡單的分享技術文件並發佈到"cloudflare",包含介紹文章: "全面瞭解 n8n v1.88.0 的重磅更新 —— MCP Server"、"教會你用 Google AI Studio 提早結束工作回家"、"C# 設計模式學習筆記與程式碼範例"、"JavaScript 設計模式學習筆記與程式碼範例"、"Functional Design Pattern 是一個結合函數式程式設計和設計模式的概念"
albertshao
Br0ski777
x402 micropayment API for AI agents. In-memory vector store with cosine similarity search. For RAG pipelines. Pay per call with USDC on Base.
UsamaK98
A lightweight python notebook mcp server that allows AI agents and other MCP clients to interact with python notebook files seamlessly.
edobez
MCP server for enabling memory for Claude through a knowledge graph
TheWinci
Persistent project memory for AI coding agents. Hybrid vector + BM25 search with AST-aware chunking (24 languages), dependency graph boosting, conversation memory, checkpoints, annotations, and wiki generation. Local-first, zero config. `bunx mimirs init`
kelnixsolutions
AI-Ready Data & Context Engineering API. Connect any data source — PostgreSQL, CRMs, APIs — and get clean, structured, AI-ready data in seconds. Natural language queries, semantic vector search, automated PII redaction, deduplication, and AI-powered context building for RAG pipel
cstamigo-droid
apifyforge
Knowledge graph causal discovery over multi-domain research data, delivered through a single Model Context Protocol interface.
pi-prakhar
pimentelleo
MCP server that gives AI agents fast access to AdonisJS documentation (v5, v6, v7).
MCP-Mirror
Mirror of
Common questions about MCP servers, tools, and integrations
An MCP server is a program built on the Model Context Protocol that wraps a tool, data source, or API — like file access, a database, or web search — into a capability an AI assistant can discover and call.
Every server's detail page includes ready-to-paste config snippets for Claude Desktop, Cursor, VS Code, and other common clients — most installs take just a couple of minutes.
Most servers listed here are free and open source. Some wrap third-party APIs (cloud services, paid data providers, etc.) that require your own API key or subscription.
A local MCP server runs on your device and usually connects over stdio, giving you more direct control over data but requiring a runtime and installation. A remote MCP server is hosted by a provider and connects over HTTP, making setup easier while adding network and provider availability dependencies.
Claude Desktop, Claude Code, Cursor, VS Code, Codex, and other AI clients that support the Model Context Protocol can connect to MCP servers. Configuration formats and supported transports vary by client.
Review the source repository, maintenance activity, dependencies, requested permissions, and data-handling documentation before installation, and prefer official or trusted maintainers. Use least-privilege credentials for sensitive access such as files, databases, shells, and production systems.