Why this server?
Provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
Why this server?
Provides functionality to fetch web content in various formats (HTML, JSON, plain text, and Markdown) through simple API calls.
Why this server?
A Model Context Protocol server that enables LLMs to interact with web pages, take screenshots, generate test code, scrape web pages, and execute JavaScript in a real browser environment.
Why this server?
An open-source MCP server that allows clients to interact with llms.txt documentation files, allowing users to control and audit context retrieval.
Why this server?
An MCP server that extends AI agents' context window by providing tools to store, retrieve, and search memories, allowing agents to maintain history and context across long interactions.
Why this server?
A Model Context Protocol server that integrates with Storybook to help AI tools query UI components and retrieve usage examples from static Storybook files.
Why this server?
MCP Compass is a discovery and recommendation service that assists AI assistants in finding and understanding Model Context Protocol servers through natural language queries.
Why this server?
Implementation of an MCP server for the Unified Cognitive Processing Framework for advanced problem-solving, creative thinking, and cognitive analysis through structured tools for knowledge mapping, recursive questioning, and perspective generation.
Why this server?
Enhances the MCP memory server by implementing PouchDB for robust document storage and enabling the creation and management of a knowledge graph that captures interactions via language models.