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Why this server?
Enables AI models to access GitHub repository contents as context, with features to fetch entire repositories, specific file contents, and repository structures for use in AI interactions.
Why this server?
A server implementation that enables AI assistants to interact with HubSpot CRM data, allowing for seamless creation and management of contacts and companies, retrieval of activity history, and access to engagement data through natural language commands.
Why this server?
A server that provides AgentQL's data extraction capabilities enabling AI agents to get structured data from unstructured web.
Why this server?
Enables interaction with GitHub repositories through the GitHub API, allowing file operations, repository management, issue tracking, and code search through natural language commands.
Why this server?
A server that provides structured access to markdown documentation from NPM packages, Go Modules, or PyPi packages, enabling informed code generation by exposing these docs as resources or tools.
Why this server?
A comprehensive Model Context Protocol server implementation that enables AI assistants to interact with file systems, databases, GitHub repositories, web resources, and system tools while maintaining security and control.
Why this server?
A server that enables interaction with YouTube data through the Model Context Protocol, allowing users to search videos, retrieve detailed information about videos/channels, and fetch comments.
Why this server?
The Tibber MCP server provides an AI agent with a convenient way to interact with the Tibber API and query information such as current energy prices and your energy consumption data.
Why this server?
Provides functionality to fetch and transform web content in various formats (HTML, JSON, plain text, and Markdown) through simple API calls.