v0.0.0 · Apache-2.0
An implementation of Model Context Protocol (MCP) server for Argo CD.
v0.3.8 · Apache-2.0
Local-first, self-hosted AI agent runtime and MCP bridge with sandboxed sessions, memory, credentials, audit/replay, and a local Console.
v0.3.8 · Apache-2.0
Local-first, self-hosted AI agent runtime and MCP bridge with sandboxed sessions, memory, credentials, audit/replay, and a local Console.
v0.13.10 · Apache-2.0
Agent-native TypeScript framework for MCP servers. Includes runtime infrastructure and agent skills for building, testing, and shipping servers.
v0.2.2 · MIT
手机平板远程 DeepSeek Harness:扫码即可继续使用电脑上的 DSH,无需远程桌面 / SSH / 公网 IP,支持一次性配对、Github授权加密登录,独立设备授权与随时撤销,实现远程连接很简单,但安全才是我们所想要的。
v3.8.5 · MIT
MCP SSH Server: 37 tools for remote SSH management | Claude Code & OpenAI Codex | DevOps automation, backups, database operations, health monitoring
v0.0.0 · MIT
Deploy static websites, landing pages, and prototypes instantly from AI agents. Start with the hosted endpoint at mcp.shipstatic.com (no install, no signup, no API key), or install this package to deploy folders from your own machine. The same fifteen too
v0.4.111 · MIT
A-Team MCP Server — build, validate, and deploy multi-agent solutions from any AI environment
— · Apache-2.0
Open source MCP Servers for AWS
— · MIT
Agent skill that turns natural language, code, Terraform/K8s, SQL, OpenAPI, AsyncAPI, Protobuf and GraphQL sources into editable, tested draw.io architecture diagrams: incremental sync, multi-view projection, drift diff, CI architecture tests, whiteboard derasterize, interactive HTML/PPTX/Mermaid exports.
— · no license
Testing and evaluation platform to chat, inspect, and debug MCP servers, MCP apps, and ChatGPT apps.
— · Apache-2.0
Ghidra MCP Server — 200+ MCP tools for AI-powered reverse engineering. GUI plugin + headless server, lazy tool loading, convention enforcement, batch operations, Ghidra Server integration, and Docker deployment.
— · MIT
MCP Aggregator, Orchestrator, Middleware, Gateway in one docker
v10.0.1 · Apache-2.0
Advanced GitLab MCP server
v2.5.1 · MIT
AWS MCP server: call any AWS API from AI assistants - SSO device-code re-login, Cloud Control API CRUD, CloudWatch logs and metrics
— · MIT
Free, open-source SQL Server and Postgres performance monitoring. Collectors, real-time alerts, graphical plan viewer, MCP server for AI analysis. Supports SQL 2016-2025, Azure SQL, AWS RDS, Postgres, Aurora Postgres.
— · no license
MCPCAN is a centralized management platform for MCP services. It deploys each MCP service using a container deployment method. The platform supports container monitoring and MCP service token verification, solving security risks and enabling rapid deployment of MCP services. It uses SSE, STDIO, and STREAMABLEHTTP access protocols to deploy MCP。
— · MIT
Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, create agent, update agent, add tool to agent, invoke
— · MIT
Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, confi
— · MIT
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: \"setup AI Runway\", \"onboard AKS cluster\", \"install AI Runway\", \"airunway setup\", \"deploy model to AKS\", \"GPU inference
v0.2.3 · MIT
🌍 Terraform Model Context Protocol (MCP) Tool - An experimental CLI tool that enables AI assistants to manage and operate Terraform environments. Supports reading Terraform configurations, analyzing plans, applying configurations, and managing state with Claude Desktop integration. ⚡️
v5.8.4 · MIT
Manage ChatGPT, Codex CLI, and Claude Code accounts and track quota in one place. Use multi-model smart routing with priority and automatic failover. Install AI tools and deploy local LLMs in one click.
— · MIT
Use when writing Playwright tests, fixing flaky tests, debugging failures, implementing Page Object Model, configuring CI/CD, optimizing performance, mocking APIs, handling authentication or OAuth, testing accessibility (axe-core), file uploads/downloads, date/time mocking, WebSockets, geolocation,
— · MIT
Labs to explore AI Models, MCP servers, and Agents with the AI Gateway powered by Azure API Management and Microsoft Foundry 🚀