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127,475 tools. Last updated 2026-05-05 17:13

"A search for information about model contests" matching MCP tools:

  • Retrieve detailed information about a specific dbt model, including compiled SQL, descriptions, column names, and types, by providing the model name.
  • Retrieve detailed information about a Panther data model, including Python body code and UDM mappings for security monitoring analysis.
    Python
    Apache 2.0
  • Retrieve detailed information about a local Ollama model, including its modelfile, parameters, and architecture. Choose output as JSON or Markdown.
    AGPL 3.0
  • Retrieve detailed specifications and configuration information for a specific Ollama model to understand its capabilities and parameters before use.
    MIT
  • Retrieve detailed information about a specific AI model version by providing its unique ID, enabling users to access and manage model data on the Civitai MCP Server.
    MIT
  • Retrieve detailed information about AI models from multiple providers to understand capabilities, specifications, and integration requirements before implementation.
    MIT

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  • Check if a task runs locally vs cloud. Save money on calls that don't need cloud inference.

  • 4 web-search tiers (x402 USDC on Base) - simple/medium/deep/cached. Free health.

  • Retrieve detailed information about a specific model using its unique ID from the Grok MCP Server, enabling efficient model management and operations.
    MIT
  • Retrieve detailed information about a specific AI model using its unique ID. Enables users to access model details through the Civitai MCP Server for informed AI assistant interactions.
    MIT
  • Retrieve detailed information about a specific Ollama model to understand its capabilities and configuration before use.
    AGPL 3.0
  • Obtain detailed information about a specific Ollama model, including configuration and metadata, to support local model management and inference without cloud dependencies.
  • Retrieve detailed information about a specific Ollama model, including its configuration, parameters, and capabilities, to understand and verify model properties before use.
    MIT
  • Search the web for current information, news, articles, and websites to find up-to-date content, research topics, or answer questions about recent events.
    Apache 2.0
  • Retrieve schema and information about a Redis search index, including fields and attributes, to support troubleshooting and optimization.
    MIT
  • Retrieve detailed information about a specific OpenStreetMap changeset, including metadata and optional discussion comments, for map data analysis and quality assurance.
    MIT
  • Retrieve detailed information about a specific path in a YDB database to understand its schema, statistics, and properties.
    Apache 2.0
  • Retrieve diagnostic information about server configuration, search paths, and warnings from the last scan to troubleshoot missing skills or verify setup.
    MIT
  • Retrieve detailed information about a specific agent, including its model, framework, category, outcome configuration, and failure risk score. Use for single agent lookup, not fleet-wide overviews.
    MIT
  • Retrieve complete metadata for any HuggingFace model, including downloads, likes, tags, library, author, pipeline task, and model card data. Provide the model ID to get detailed information.