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Utilizing Local LLMs for Query Preprocessing with Minions Framework

  • Why this server?

    This MCP server allows you to run your own local LLM and then preprocess queries before sending them to the remote server.

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    Enables seamless integration between Ollama's local LLM models and MCP-compatible applications, supporting model management and chat interactions.
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    13
    TypeScript
    MIT License
  • Why this server?

    Leverages Together AI for image generation, aligning with the concept of utilizing external models.

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    Enables the generation of images using Together AI's models through an MCP server, supporting customizable parameters such as model selection, image dimensions, and output directory.
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    JavaScript
    MIT License
    • Apple
    • Linux
  • Why this server?

    Although it's an image processing MCP server, it allows for workflow configurations that could involve preprocessing steps.

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    The Comfy MCP Server uses the FastMCP framework to generate images from prompts by interacting with a remote Comfy server, allowing automated image creation based on workflow configurations.
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    Python
    MIT License
  • Why this server?

    This server facilitates access to various AI models through a unified interface, potentially allowing for local preprocessing before querying external models.

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    Provides integration with OpenRouter.ai, allowing access to various AI models through a unified interface.
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    TypeScript
    Apache 2.0
  • Why this server?

    This server uses various AI models to provide enhanced AI responses, making it a versatile option for query processing.

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    This server integrates DeepSeek and Claude AI models to provide enhanced AI responses, featuring a RESTful API, configurable parameters, and robust error handling.
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    TypeScript
  • Why this server?

    This MCP server uses Google's OR-Tools constraint programming solver with Large Language Models, allowing users to manage and configure large language model interactions seamlessly.

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    This server facilitates the invocation of AI models from providers like Anthropic, OpenAI, and Groq, enabling users to manage and configure large language model interactions seamlessly.
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    Python
    MIT License
  • Why this server?

    This server enables LLMs to perform semantic search and document management using ChromaDB, potentially allowing it to perform query processing functions locally.

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    Enables LLMs to perform semantic search and document management using ChromaDB, supporting natural language queries with intuitive similarity metrics for retrieval augmented generation applications.
    Python
    • Apple
  • Why this server?

    A server that performs image analysis and processing with the model Moondream, enabling advanced image analysis.

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    A powerful server that integrates the Moondream vision model to enable advanced image analysis, including captioning, object detection, and visual question answering, through the Model Context Protocol, compatible with AI assistants like Claude and Cline.
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    JavaScript
    Apache 2.0
  • Why this server?

    Facilitates easy running, building, training, and deploying of ML models to the cloud.

    Brevofficial

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    Run, build, train, and deploy ML models on the cloud.
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    Python
    • Apple
  • Why this server?

    Allows using HuggingFace Spaces directly from Claude to apply a large variety of ML models.

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    Use HuggingFace Spaces directly from Claude. Use Open Source Image Generation, Chat, Vision tasks and more. Supports Image, Audio and text uploads/downloads.
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    TypeScript
    MIT License
    • Apple