"AI-Powered Virtual Medical Consultation Assistant" matching MCP servers:

Enables AI-powered PLC programming with natural language to ladder logic conversion, L5X and .ACD project generation, and semantic search through L5X files and documentation.

Assists AI developers with intelligent requirement analysis and architecture design through guided clarification questions, branch-aware management, and automated architecture generation with persistent storage.

Enables AI-powered interaction with Metabase instances and PostgreSQL databases through natural language. Creates models, SQL queries, metrics, and dashboards using both Metabase API and direct database connections.

Exposes a single HTTP endpoint that aggregates tool definitions from GitHub, Kubernetes, and database namespaces, letting clients list available tools and invoke them by name. It provides health-check, tool-discovery, and tool-call routes for local, read-only experimentation without calling hosted models or applying production changes.

Access a 24/7 AI senior developer with 26 specialized tools for the full software development lifecycle. Use tools like explain_code, debug_code, and refactor_code to analyze, debug, and optimize your codebase instantly. Deploy github_fix_issue and create_pr for seamless GitHub automation, or get ai_development_advice for architecture and career guidance.

Enables interaction with OpenAI's Chat Completion and Assistants APIs, supporting assistant management, file operations, and direct queries to GPT models through standardized MCP tools.

A lightweight MCP canary for ModelScope hosted STDIO that verifies package installation, MCP initialization, and tool discovery without loading models or medical data.

An MCP server that lets AI coding agents work on Godot 4 projects, including reading and editing scenes, writing and validating GDScript, running the game, and capturing screenshots.

MCP server for managing Terraform infrastructure as code, enabling initialization, planning, applying, destroying, validating, and showing state of Terraform configurations.

An MCP server that allows users to define custom tools via a configuration file for tasks such as retrieving project architecture and managing task lists. It also includes a plugin for generating structured and optimized AI prompts based on specific context sections and instructions.

Enables AI agents to safely work on Windows developer workstations through governed, project-scoped filesystem access, durable command execution, bounded search, Windows operations, and resource-aware runtime controls. It also supports optional developer-context backends for code navigation, repository graph exploration, and memory retrieval.

Automatically generates Chinese README documentation and mind maps for project folders, enabling intelligent documentation management and project structure visualization.

MCP server that connects LLMs to Kubernetes clusters for troubleshooting, scanning failing pods, diagnosing root causes, and applying guarded fixes or generating manifests via natural language.

Manages the lifecycle of MCP services with health monitoring, auto-restart capabilities, and process tracking. Enables users to start, stop, restart, and monitor MCP services through natural language commands.

Automatically analyzes Python codebases and generates professional documentation including README, API docs, and setup guides.

An advisory and generative copilot for Terraform that reviews existing scripts and generates compliant infrastructure using organization-specific rules.

Enables natural-language management of Kubernetes clusters via kubectl-ai and Gemini, providing commands like listing pods, scaling deployments, and retrieving logs through a FastAPI backend.

Enables natural language interactions with Jira for creating issues, managing boards, searching tickets, and handling project operations. Supports conversational AI workflows with smart field detection and multi-turn conversations.

Connects a local LLM (Ollama) to a SQLite database via the Model Context Protocol, enabling natural language queries and controlled read/write database operations through MCP tools.

Multi-agent swarm orchestrator for AI workflows. Exposes blackboard read/write, agent dispatch, permission gating (AuthGuardian), token budget enforcement (FederatedBudget), and audit log tools over MCP. Supports 14 AI framework adapters including LangChain, AutoGen, CrewAI, Codex, and A2A — mix any frameworks in one swarm with race-condition-safe shared state.(Traffic light for agents)