"Proof-of-Concept Examples for Multi-Component Processes (Model Context Protocol)" matching MCP servers:

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

Enables AI assistants to autonomously perform site reliability engineering including monitoring, root-cause analysis, impact assessment, and remediation with cryptographic zero-trust enforcement.

An MCP server that bridges multiple AI clients (Claude, Gemini, Codex, OpenCode) so they can call each other as tools.

Orchestrates multiple AI coding agents declaratively to automate software development workflows for engineering teams.

104 high quality skill packs across 20+ tech stacks. 1,284 curated chunks. 104 validated discoveries. Every piece reviewed, cross-validated, and myth-busted.

An MCP-powered AI agent that audits your Gmail for recurring subscriptions, detects silent price increases, and flags unused services.

An MCP server that bridges multiple LLMs (OpenAI-compatible APIs and CLI coding agents) for collaborative debugging and diverse AI perspectives.

A minimal MCP server template that offers calculator tools, resources, and prompts for learning NitroStack fundamentals, built with TypeScript and Zod.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

A Model Context Protocol server built with FastMCP that provides tools for retrieving the current local date and time. It allows LLMs to access precise temporal information directly from the host environment.

Bridges a local AI agent to a Colab session in the browser, enabling code execution and file operations through the Model Context Protocol.

Enables multi-LLM deliberation via a council of panel members, judges responses for consensus and contradictions, and returns analysis to the calling model.

MCP server exposing TASIE's autonomous SAST, live exploit, and human-gated remediation as tools, enabling ChatGPT clients to scan code, dependencies, and frameworks and receive proof-carrying fixes.

Enables LLMs to search and retrieve detailed information from the Turkish Patent and Trademark Office (TÜRKPATENT) database for trademarks, patents, and industrial designs. It provides comprehensive intellectual property research tools through the Model Context Protocol.

Enables AI agents to discover verifiable DeFi yield opportunities, generate algorithmic portfolio plans, and track cryptographic proof receipts, bridging LLMs with blockchain yield protocols.

A multi-domain MCP server that exposes a small, stable surface of three tools (list_domains, list_domain_tools, call_domain_tool) to gate access to various tool domains like Plane and BloodBank, preventing agent schema overload.

Provides AI assistants with direct access to the complete Godot Engine documentation, including classes, tutorials, and features. It enables developers to retrieve and analyze official documentation through natural language interfaces using the Model Context Protocol.

MCP server for Overseerr media request management. Enables AI assistants to search for media, view requests, and manage media requests through the Model Context Protocol.

A Python MCP server that enables AI assistants to manage Todoist tasks and projects through the Model Context Protocol. It supports full CRUD operations for tasks and projects, including support for nested projects and Todoist's advanced filter syntax.

A Model Context Protocol server that provides programmatic APIs for running mutation tests with mutmut, analyzing results, and improving test coverage in Python projects.