"Guide to Deploying a Large Language Model Framework" matching MCP servers:

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 minimal MCP server that enables HTTP requests with any method, headers, and body types, supporting large responses through chunked transfers with disk-backed caching.

Provides a constitutional governance framework for AI agents, offering 13 MCP tools for session initiation, reasoning, evidence fetching, judgment, and execution, all governed by hard invariant laws and a hierarchical set of constitutional floors.

An MCP server framework featuring dynamic tool loading and a modular one-tool-per-file architecture for rapid development. It supports both Stdio and HTTP transport modes, offering automated test generation and centralized configuration management.

A Python MCP server that provides language models full read/write access to a Node-RED instance through its Admin HTTP API, enabling flow management with structured Pydantic responses and incremental patching.

A Model Context Protocol server framework featuring dynamic tool loading and automatic tool discovery from a dedicated directory. It leverages FastMCP to provide a robust environment for building, configuring, and testing individual Python-based tools.

Bridges Confluence Wiki with Large Language Models, allowing them to search, read, and explore content through automated HTML-to-Markdown conversion. It supports both local stdio and containerized HTTP/SSE transport modes for flexible deployment.

A template and demonstration project for building, testing, and deploying remote MCP servers using FastMCP and uv. It provides a foundational structure for creating MCP-compliant tools that can be hosted publicly and integrated with LLM agents.

A Model Context Protocol server built with FastMCP that enables dynamic tool loading and configuration from individual Python files. It provides a flexible framework for automatically discovering, testing, and running tools via Stdio or HTTP transport modes.

Enables AI assistants to orchestrate multi-step workflows by converting natural language into executable plans, coordinating tools, agents, and services via the Model Context Protocol.

MCP server for business-day arithmetic with country-aware holiday calendars. It offers tools to check, calculate, and list business days and holidays for over 60 countries.

Enables Claude to plan trips by performing live searches against Google Flights, hotels, vacation rentals, activities, and events, plus weather and currency conversion.

Query PainSpotter to discover validated business opportunities and trending pain points mined from Reddit, Hacker News, and Product Hunt.

A personal memory engine and MCP server that stores durable facts in markdown files managed via git, enabling hybrid search (lexical + semantic) through an MCP interface for persistent context across LLM sessions.

Connects AI agents to ROS 2 robots via rosbridge, enabling observation, inspection, and control of robot topics, services, and actions through natural language.

Enables AI assistants to search and filter Azure platform updates, including previews, general availability, and retirements, through natural language queries.

Enables querying git commit history to analyze when and why code changes happened, providing authorship context and diffs for specific modules.

Provides access to Atomic Red Team tests, enabling search, validation, and execution of atomic tests via natural language.

Spawn parallel autonomous AI agent sessions from a single MCP client. Each agent gets its own workspace, tools, and execution context.

An open-source MCP server for live Apple App Store competitor research, enabling AI agents to search apps, fetch metadata, compare competitors, and retrieve reviews and top charts as structured JSON.