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

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    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.
    3
    27
    Apache 2.0
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    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.
    2
    MIT
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    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.
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    AGPL 3.0
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    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.
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    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.
    22
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    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.
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    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.
    3
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    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.
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    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.
    1
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    Enables AI assistants to search and filter Azure platform updates, including previews, general availability, and retirements, through natural language queries.
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    MIT
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    This MCP server provides comprehensive Google Workspace integration (Gmail, Drive, etc.) with multi-user OAuth. Unique features include RAG-powered natural language to Chat card rendering, runtime Jinja2 macro creation, and dynamic tool management.
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    Apache 2.0
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    Enables AI assistants to query, analyze, and discover FileMaker database schemas via OData v4, with pandas-powered analytics for efficient data summaries.
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    GPL 3.0
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    An MCP server that provides AI agents with ICP Triangulation Framework™ for scoring prospects across firmographics, behaviors, and growth signals, plus RFM analysis and pipeline health scoring, with optional HubSpot integration.
    3
    Business Source 1.1
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    Enables AI assistants to interact with Intervals.icu fitness tracking and wellness data, allowing users to fetch, filter, and group activities or health metrics. It provides structured summaries of workouts and physical well-being through natural language queries.
    4
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    Enables AI assistants to query KumoRFM for predictive analytics on relational data, including graph management, natural language to PQL conversion, and training-free predictions.
    12
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    MIT
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    Exposes a Kubernetes cluster to MCP-compatible AI clients, enabling read-only and optional write operations on cluster resources like pods, deployments, and namespaces through natural language.
    9
    1
    MIT
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    Provides CodeQL language intelligence to AI agents via MCP, enabling completions, hover, definitions, references, diagnostics, formatting, and in-memory file updates for QL code.
    7
    MIT
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    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.
    9
    MIT