MCP Servers

The firewall for AI agents. Open-source policy enforcement for MCP. Website: policylayer.com Intercept is a deterministic enforcement proxy for the Model Context Protocol (MCP). It sits between an AI agent and an MCP server, evaluating every tools/call request against YAML-defined policies. Violating calls are blocked at the transport layer before reaching the upstream server. MCP gives AI agents

A Model Context Protocol (MCP) server for maigret, a powerful OSINT tool that collects user account information from various public sources. This server provides tools for searching usernames across social networks and analyzing URLs. It is designed to integrate seamlessly with MCP-compatible applications like Claude Desktop. This tool is designed for legitimate OSINT research purposes. Please: -

A Model Context Protocol (MCP) compliant server that formats files using .editorconfig rules. This project started from a specific workflow issue I kept running into. I found that while working with AI coding agents, they would often generate code with minor formatting errors, like trailing whitespace or inconsistent newlines. Our linters would then flag these issues, and the agent would spend val

OpenMCP is both: 1. a standard for converting web APIs into MCP servers 2. an open source registry of servers which follow the standard Each OpenMCP server gives MCP clients the ability to make requests to a particular web API in a token-efficient way. Together the servers in the registry represent a broad range of services, empowering the underlying client LLMs to fetch data and perform actions o

Read the introduction here llmindset.co.uk/resources/mcp-hfspace/ Connect to Hugging Face Spaces with minimal setup needed - simply add your spaces and go! By default, it connects to black-forest-labs/FLUX.1-schnell providing Image Generation capabilities to Claude Desktop. NPM Package is @llmindset/mcp-hfspace. Install a recent version of NodeJS for your platform, then add the following to the mc

A powerful Model Context Protocol (MCP) server that provides AI-powered image and video analysis using Google Gemini and Vertex AI models. - Dual Provider Support: Choose between Google Gemini API and Vertex AI - Multimodal Analysis: Support for both image and video content analysis - Flexible File Handling: Upload via multiple methods (URLs, local files, base64) - Storage Integration: Built-in Go

Publish the package to npmjs by bumping version, building, and creating a GitHub release

The Quickchat AI MCP (Model Context Protocol) server allows you to let anyone plug in your Quickchat AI Agent into their favourite AI app such as Claude Desktop, Cursor, VS Code, Windsurf and more. 1. Create a Quickchat AI account and start a 7-day trial of any plan. 2. Set up your AI's Knowledge Base, capabilities and settings. 3. Go to the MCP page to activate your MCP. Give it Name, Description

MCP server for Google Keep 1. Add the MCP server to your MCP servers: 2. Add your credentials: GOOGLEEMAIL: Your Google account email address GOOGLEMASTERTOKEN: Your Google account master token Check https://gkeepapi.readthedocs.io/en/latest/obtaining-a-master-token and https://github.com/simon-weber/gpsoauth?tab=readme-ov-filealternative-flow for more information. find: Search notes with optional

✨ Features | 🚀 Getting Started | 🎥 Demos | ⚙️ Configuration | 🛠️ Tools | 🧑‍💻 Development A powerful and flexible Kubernetes Model Context Protocol (MCP) server implementation with support for Kubernetes and OpenShift. - ✅ Configuration: - Automatically detect changes in the Kubernetes configuration and update the MCP server. - View and manage the current Kubernetes .kube/config or in-cluster

A Model Context Protocol (MCP) server that extracts component information from Storybook design systems. Connects to Storybook instances and extracts HTML, styles, and component metadata. With self-signed certificate: Then configure in your MCP client (see Environment Variables). - Puppeteer: Uses headless Chrome for dynamic JavaScript component rendering - Chrome/Chromium: Required for Puppeteer

A Kubernetes MCP (Model Control Protocol) server that enables interaction with Kubernetes clusters through MCP tools. - Query supported Kubernetes resource types (built-in resources and CRDs) - Kubernetes resource operations with fine-grained control - Read operations: get resource details, list resources by type with filtering options - Write operations: create, update, and delete resources (each

This MCP server provides secure access to the local filesystem via the Model Context Protocol (MCP). - Name: File System - Description: Access to files and directories on the local file system - Read the complete contents of a file from the file system - Parameters: path (required): Path to the file to read - readmultiplefiles - Read the contents of multiple files in a single operation - Parameter

An MCP server focused only on Overleaf projects (via Overleaf Git sync). .env example: - OVERLEAFTOKEN is required. - projectid can be passed per tool call, or use default PROJECTID. - Overleaf Git access requires a plan that supports Git integration. Add to ~/.config/Claude/claudedesktopconfig.json: - Python 3.13+ - uv package manager MIT - See LICENSE

This project provides Model Context Protocol (MCP) for the Mifos X Ecosystem, enabling AI agents to access financial data and operations. Implementations is available in Java (Quarkus). Use the MCP Inspector to test and debug your server: This starts a local web UI to connect to your MCP server via STDIO or SSE. Prerequisites: JDK 21+, Maven 1. Configure environment variables in your shell or IDE:

An MCP (Model Context Protocol) server that enables running Bruno collections. This server allows LLMs to execute API tests using Bruno and get detailed results through a standardized interface. Run Bruno collections using the Bruno CLI Support for environment files Support for environment variables Detailed test results including: Overall success/failure status Test summary (total, passed, failed

A PTY-based MCP server with strong Windows support, giving MCP-capable AI clients and their agents persistent, interactive shell access via pseudo-terminals (node-pty). Unlike simple exec-based approaches, this keeps PTY-backed shell sessions alive across steps, with bidirectional communication for interactive CLI tools, incremental reads, and session state that carries forward. See the Changelog

Instead of manually writing a system prompt, this tool mines your actual conversation history — your word patterns, recurring topics, and habits of thought — and distils them into a ~3k character profile that meaningfully changes how an AI responds to you. The pipeline runs entirely locally. It never sends your conversation data anywhere. 1. Stream conversations-.json using ijson — never loads the

A Model Context Protocol (MCP) server for the Discord API (JDA), allowing seamless integration of Discord Bot with MCP-compatible applications like Claude Desktop. Enable your AI assistants to seamlessly interact with Discord. Manage channels, send messages, and retrieve server information effortlessly. Enhance your Discord experience with powerful automation capabilities. Manual Installation M

stats-compass-mcp Turn your LLM into a data analyst. Multiple data science tools via MCP. Restart your client and start asking questions about your data. Run stats-compass-mcp list-tools to see all available tools. Start your message with "Use stats compass to..." — this tells the AI to use the Stats Compass tools instead of trying to write code or use other methods. Local mode: Start with "Use st

Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor. This is especially useful for developing desktop applications that require complex user interactions to test. For the best results, add the following to your custom prompt: This will ensure Cline uses this MCP server to request user feedback before marking the task as completed. Hitting Save Configuration crea

Manage MCP servers across 13 AI clients from one CLI. Define a server once. Enable it where you want. Keep unmanaged client entries intact. MCP servers are useful, but managing them across multiple AI clients is repetitive and error-prone: - different config locations - different formats (JSON, JSONC, TOML) - repeated env/header setup - easy to overwrite manual client entries - hard to roll back a

A remote Model Context Protocol (MCP) server that connects AI assistants to your crash reporting and real user monitoring data in Raygun through natural language conversations. 📚 Tool Reference • 🚀 Quick Start • 🔑 Get API Token - 🐛 Error Management - Investigate, resolve, and track application errors and crashes with full stack traces and context - 🚀 Deployment Tracking - Monitor releases and

Slack MCP Server Give Claude the same Slack access you have. DMs, threads, history—no admin approval. I built this because I was working with someone to help me manage a complex workload, and we kept hitting walls. They needed context from my messages—"what did X say about Y?"—but Slack's API blocks access to DMs without admin approval. Screenshotting messages is not a workflow. This server bridge