Open Source Mac Model Context Protocol (MCP) Servers
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Model Context Protocol (MCP) Servers for Mac
View 1813 business solutionsBrowse free open source Model Context Protocol (MCP) Servers and projects for Mac below. Use the toggles on the left to filter open source Model Context Protocol (MCP) Servers by OS, license, language, programming language, and project status.
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InEight is a leader in construction project controls softwareMinimize risks, gain operational efficiency, control project costs, and make confident, informed decisions. InEight software has your back during every stage of construction, from accurate pre-planning to predictable execution and completion. When project teams collaborate effectively, every decision is backed by precise, authoritative insights.
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The ultimate digital workspace.Hundreds of companies and millions of employees use Axero’s intranet software to communicate, collaborate, manage tasks and events, organize content, and develop their company culture.
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xiaohongshu-mcp
MCP for xiaohongshu.com
xiaohongshu-mcp is a Model Context Protocol (MCP) server that equips AI assistants with first-class tools for working on Xiaohongshu (Little Red Book), focusing on day-to-day creator and operator workflows rather than generic browsing. The project centers on authenticated actions and data access that matter to content operations, such as checking login state, publishing or scheduling content, fetching recommendations and search results, reading post details, and acting on comments. It’s packaged so MCP-capable clients (e.g., Claude Desktop, Cursor) can discover its tools via schemas instead of prompt guesswork, which improves reliability and reduces brittle automation. The repo highlights a growing community and provides links to a hosted landing page, signaling that the server is intended for practical use beyond a proof of concept. By exposing typed resources and procedures, it enables repeatable, auditable automation in social workflows where UI changes are frequent. -
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MarkItDown
Python tool for converting files and office documents to Markdown
MarkItDown is a lightweight Python utility developed by Microsoft for converting various files and office documents to Markdown format. It is particularly useful for preparing documents for use with large language models and related text analysis pipelines. -
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MCP Grafana
MCP server for Grafana
The Grafana MCP Server is a Model Context Protocol (MCP) server designed to provide access to Grafana instances and their surrounding ecosystems. It enables seamless integration with Grafana's visualization and monitoring capabilities. -
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ScreenPipe
AI app store powered by 24/7 desktop history. open source
Screenpipe is an AI app store powered by continuous desktop history recording. It operates entirely locally, offering developers a platform to build, distribute, and monetize AI applications that leverage comprehensive contextual data from users' desktop activities. -
Taking the Paper Out of WorkThe Square 9 AI-powered intelligent document processing platform takes the paper out of work and makes it easier to get things done with digital workflows.
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Wanaku
Wanaku MCP Router
Wanaku is an MCP Router designed to connect AI-enabled applications using the Model Context Protocol. Built on top of Apache Camel and Quarkus, it offers unmatched connectivity, speed, and reliability for AI agents, facilitating seamless integration across various services and platforms. -
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MCPTools
A command-line interface for interacting with MCP
mcptools is a command-line interface designed for interacting with Model Context Protocol (MCP) servers using both standard input/output and HTTP transport methods. It allows users to discover and call tools, list resources, and interact with MCP-compatible servers. The tool supports various output formats and includes features like an interactive shell, project scaffolding, and server alias management. -
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n8n-MCP
A MCP for Claude Desktop / Claude Code / Windsurf / Cursor
n8n-mcp is a Model Context Protocol (MCP) server that turns the n8n workflow platform into a set of first-class, typed tools an AI assistant can understand and operate. It exposes structured knowledge of n8n nodes and operations so an agent can reason about workflows, parameters, and executions without scraping docs or guessing API shapes. The server focuses on making Claude Desktop (and other MCP-capable clients) “n8n-literate,” enabling tasks such as inspecting existing workflows, proposing node chains, and validating configuration before runs. It ships with organized resources and tool definitions that map cleanly to n8n’s ecosystem, improving reliability compared with ad-hoc prompt patterns. The project targets practical agent ops: safer mutations, better error reporting, and predictable behavior when automating or refactoring automations. Community posts highlight the goal of giving agents accurate knowledge of hundreds of n8n nodes and keeping that knowledge fresh as n8n evolves. -
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GitHub MCP Server
GitHub's official MCP Server
The GitHub MCP Server exposes GitHub as a Model Context Protocol server so AI assistants can safely act on repos, issues, pull requests, gists, and more through a consistent tool interface. It’s designed to run locally or remotely and then be attached to MCP-capable clients (for example, Copilot Chat) so an LLM can search code, open files, create branches, draft PRs, label or triage issues, and query metadata without hard-coding GitHub APIs. The server defines tools and resources with fine-grained scopes, leaning on GitHub’s auth to enforce least privilege and auditable access. It supports both stdio and HTTP transports, enabling IDE and headless integrations, and adopts common MCP behaviors like prompts, schemas, and tool definitions to keep agent calls predictable. Documentation covers setup, tokens, and client configuration, highlighting native editor integrations. Its design goal is to give AI agents first-class, governed access to GitHub workflows. -
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Last9 MCP Server
Last9 MCP Server
The Last9 MCP Server is a Model Context Protocol server implementation for Last9, enabling AI agents to seamlessly bring real-time production context—logs, metrics, and traces—into local environments to auto-fix code faster. -
Securden Password VaultStore, manage, and share passwords, files, SSH keys, and DevOps secrets among IT teams. Enforce password security best practices. Ensure compliance with industry standards using comprehensive audit trails.
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Lemonade
Lemonade helps users run local LLMs with the highest performance
Lemonade is a local LLM runtime that aims to deliver the highest possible performance on your own hardware by auto-configuring state-of-the-art inference engines for both NPUs and GPUs. The project positions itself as a “local LLM server” you can run on laptops and workstations, abstracting away backend differences while giving you a single place to serve and manage models. Its README emphasizes real-world adoption across startups, research groups, and large companies, signaling a focus on practical deployments rather than toy demos. The repository highlights easy onboarding with downloads, docs, and a Discord for support, suggesting an active user community. Messaging centers on squeezing maximum throughput/latency from modern accelerators without users having to hand-tune kernels or flags. Releases further reinforce the “server” framing, pointing developers toward a service that can be integrated into apps and tools. -
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MCPHost
A CLI host application that enables Large Language Models (LLMs)
mcphost is a command-line host application that enables Large Language Models (LLMs) to interact with external tools through the Model Context Protocol (MCP). It provides a unified interface for engaging with various AI models and supports integration with multiple MCP servers, streamlining the development of AI-driven applications. -
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Playwright MCP
Playwright MCP server
An MCP server developed by Microsoft that offers browser automation capabilities using Playwright, enabling LLMs to interact with web pages through structured accessibility snapshots without relying on visual data. -
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ContextForge MCP Gateway
A Model Context Protocol (MCP) Gateway & Registry
MCP Context Forge is a feature-rich gateway and registry that federates Model Context Protocol (MCP) servers and traditional REST services behind a single, governed endpoint. It exposes an MCP-compliant interface to clients while handling discovery, authentication, rate limiting, retries, and observability on the server side. The gateway scales horizontally, supports multi-cluster deployments on Kubernetes, and uses Redis for federation and caching across instances. Operators can define virtual servers, wire multiple transports, and optionally enable an admin UI for management and monitoring. Packaged for quick starts via PyPI and Docker, it targets production reliability with health checks, metrics, and structured logs. The project positions itself as an integration hub so agentic apps can “connect once, use many” backends with consistent policy and lifecycle control. -
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FastMCP
The fast, Pythonic way to build Model Context Protocol servers
FastMCP is a fast, Pythonic framework for building servers and clients using the Model Context Protocol (MCP). It abstracts away protocol complexity like serialization, validation, and error handling, letting developers focus entirely on their business logic. With simple decorators, you can expose Python functions as tools, resources, or prompts that AI agents can safely and efficiently use. FastMCP introduces clear abstractions—components, providers, and transforms—that make it easy to control what agents see and how they interact with your system. The framework is opinionated by design, ensuring best practices and protocol compliance are the default rather than an extra burden. Actively maintained and widely adopted, FastMCP powers a majority of MCP servers and has become the de facto standard for production-ready MCP applications. -
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MCP Browser Kit
MCP Server for interacting with manifest v2 compatible browsers
An MCP server that integrates with browser extensions to enable AI assistants to interact with the user's browser, allowing actions like starring repositories on GitHub through natural language commands. -
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All-in-One Model Context Protocol
All-in-one MCP server with AI search, RAG
The All-in-One Model Context Protocol Server is a comprehensive MCP server implementation integrating services like GitLab, Jira, Confluence, YouTube, and more. It provides AI-powered search capabilities and utility tools to enhance development workflows. -
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Firecrawl MCP Server
Adds powerful web scraping and search to Cursor and Claude
firecrawl-mcp-server is the official MCP integration for Firecrawl that brings high-recall web scraping, crawling, and search into IDEs and agent runtimes. It exposes tools for single-page scrape, multi-URL batch jobs, site discovery, and search enrichment, returning cleaned, structured content suitable for downstream LLM reasoning. The server is designed to run with Firecrawl’s hosted API or self-hosted deployments, making it flexible for enterprise data-governance requirements. Built-in behaviors include JavaScript rendering, automatic retries, and streamable HTTP so long pages and large crawls can flow incrementally into agents. Because it’s an MCP server, clients get typed inputs/outputs and standardized error handling rather than ad-hoc prompt instructions. The repository is active, widely starred, and includes quick starts that make it easy to add web research to an agent stack. -
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firerpa LAMDA
The most powerful Android RPA agent framework
lamda is an Android RPA agent framework that provides visual remote desktop control and automation at scale, geared toward testing, automation validation, and device management. It exposes a clean UI to monitor and interact with connected devices and includes tooling to script actions reliably across apps and OS versions. The project emphasizes low-friction setup and powerful control primitives so teams can move from interactive validation to repeatable automation. A public wiki, releases, and issue tracker show active development across areas like connectivity, instrumentation compatibility, and robustness under detection. Together with companion projects (e.g., a device hub), lamda is positioned as a next-generation mobile automation stack rather than a single tool. Its focus on remote control plus RPA primitives makes it useful for QA, operations, and large-scale device orchestration. -
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DeepSource MCP Server
Model Context Protocol (MCP) server for DeepSource
The DeepSource MCP Server enables AI assistants to interact with DeepSource's code quality analysis capabilities through the Model Context Protocol. It allows retrieval of code metrics, access to issues, quality status checks, and analysis of project quality over time. -
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HexStrike AI MCP Agents
HexStrike AI MCP Agents is an advanced MCP server
HexStrike AI is an MCP server that lets LLM agents autonomously operate a large catalog of offensive-security tools. Its goal is to bridge “language models” and practical pentest workflows—enumeration, exploitation, vulnerability discovery, and bug bounty reconnaissance—under safe, auditable controls. The server exposes typed tools and guardrails so agent prompts translate to concrete, parameterized actions rather than brittle shell strings. It ships with curated tool adapters, task orchestration, and guidance for connecting popular agent clients (Claude, GPT, Copilot) to a hardened execution environment. Documentation highlights the breadth of supported utilities and positions HexStrike as a research and red-team aid, not a point-and-click exploit kit. A public site and active repository activity signal an expanding community around autonomous security research agents. -
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Actors MCP Server
Model Context Protocol (MCP) Server for Apify's Actors
The Apify Actors MCP Server is a Model Context Protocol (MCP) server that enables AI assistants to interact with Apify Actors. This integration allows AI models to utilize various web scraping and automation tools provided by Apify, facilitating tasks such as data extraction and web automation. -
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IDA Pro MCP
MCP Server for IDA Pro
The IDA Pro MCP Server is a Model Context Protocol (MCP) server designed to integrate with IDA Pro, a popular disassembler and debugger. It enables AI assistants to interact with IDA Pro, facilitating tasks such as code analysis and reverse engineering. -
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Search1API MCP
A Model Context Protocol (MCP) server
The Search1API MCP Server is a Model Context Protocol server that provides search and crawl functionality using Search1API. It enables web and news searches, content extraction, and sitemap retrieval, integrating seamlessly with MCP clients. -
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XcodeBuildMCP
A Model Context Protocol (MCP) server
XcodeBuildMCP is a Model Context Protocol server that exposes Xcode operations as typed tools and resources so AI assistants can build, test, and debug iOS apps programmatically. It’s organized with a modern plugin architecture and workflow-scoped tool directories, covering common developer actions across projects, schemes, targets, simulators, real devices, and Swift packages. The server aims to be “agent-ready,” surfacing capabilities (build, clean, test, archive, install, run, log collection) with explicit schemas instead of brittle prompt instructions. It supports MCP transports suitable for local IDEs and service deployments, and pairs with a public website that positions it as a bridge between Xcode and autonomous assistants. Documentation and marketing materials emphasize end-to-end flows such as fixing build errors, managing simulators, and deploying to devices via natural-language requests. -
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FastAPI-MCP
Expose your FastAPI endpoints as Model Context Protocol (MCP) tools
fastapi_mcp lets you expose existing FastAPI endpoints as Model Context Protocol (MCP) tools with minimal setup, so AI agents can call your app as first-class tools. Rather than acting as a thin converter, it’s built as a native FastAPI extension that understands dependency injection, so you can reuse Depends() for authentication and authorization across your MCP tools. The server speaks directly to your app over its ASGI interface, avoiding extra HTTP hops between the MCP layer and your API, which reduces latency and simplifies deployment. A tiny bootstrap is enough to stand up an MCP server and, if desired, mount an HTTP transport for remote clients. The docs emphasize a FastAPI-first workflow: keep your schemas, reuse your middleware, and surface endpoints to agents without rewriting controllers. The project is active, with examples and a dedicated site that shows getting started, security, and transport options.
