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Enables agents to test language model prompts with different providers and configurations.
Provides a robust Model Context Protocol (MCP) server for Home Assistant, enabling comprehensive programmatic management of smart home entities, automations, services, and dashboards.
Generates a Multi-Agent Conversation Protocol (MCP) server for the Zoom API from an OpenAPI specification.
Evaluates functionality using the Claude language model.
Provides specialized tools for validating and retrieving metadata from Markdown files crucial to the Subordinación y Valor research project.
Provides natural language access and query capabilities for a MongoDB movie database.
Provides Ethereum blockchain data tools via Etherscan's API for interacting with blockchain data.
Provides weather data using the Open-Meteo API, enabling AI assistants to retrieve current conditions and forecasts globally.
Executes authorized shell commands remotely with support for standard input and comprehensive output.
Provides a testing ground for validating and demonstrating server-side operations and integrations.
Enables AI IDEs and agents to securely query Graylog instances via the Model Context Protocol.
Integrate Todoist task, project, and label management with AI assistants via a Model Context Protocol server.
Enables Claude to interact with the CVEX trading platform for market data access, account management, and trade execution.
Enhances Model Context Protocol workflows with robust caching, retry logic, batch operations, and rate limiting capabilities.
Enables AI models to interact with MySQL databases through a standardized Model Context Protocol (MCP) interface.
Facilitates searching and querying documentation and GitHub code examples for the Onyx programming language.
Exposes Canvelete's design capabilities to AI assistants and other MCP-compatible clients for programmatic design creation and manipulation.
Demonstrates developing and running serverless applications using the Model Context Protocol (MCP) with Netlify Functions and Express.js.
Enables searching YouTube content through various implementation approaches, including direct API calls and the Model Context Protocol (MCP).
Enables AI assistants to manage infrastructure, applications, databases, services, and more through a self-hosted Coolify PaaS platform.
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