Why this server?
MCP-Ragdocs integrates with Langchain to answer questions about documentation through vector search and enables AI assistants to augment their responses with relevant documentation context
Why this server?
Use HuggingFace Spaces directly from Claude. Use Open Source Image Generation, Chat, Vision tasks and more. Supports Image, Audio and text uploads/downloads.
Why this server?
Provides a project memory bank and RAG context provider for enhanced code understanding and management through vector embeddings, integrated with RooCode and Cline.
Why this server?
Enables users to search for academic articles on platforms like arXiv using specific keywords, with plans to integrate more scholarly databases in the future.
Why this server?
Enables retrieval and processing of web page content for LLMs by converting HTML to markdown, with support for content truncation and pagination.
Why this server?
This is a Model Context Protocol (MCP) server adaptation of LangChain Ollama Deep Researcher. It provides the deep research capabilities as MCP tools that can be used within the model context protocol ecosystem, allowing AI assistants to perform in-depth research on topics (locally) via Ollama
Why this server?
Enables AI assistants to enhance their responses with relevant documentation through a semantic vector search, offering tools for managing and processing documentation efficiently.
Why this server?
A simple Model Context Protocol (MCP) server that integrates with Notion's API to manage my personal todo list through Claude.
Why this server?
Enables efficient web search integration with Jina.ai's Search API, offering clean, LLM-optimized content retrieval with support for various content types and configurable caching.