"Most downloaded items or content" matching MCP servers:

Crawl any website into clean Markdown, search through pages, read full content, and extract structured data using OpenAI, Claude, Gemini, or Grok — with auto-citation and resume support.

Enables LLMs to chat with long PDFs using a reasoning-based, tree-structured document index that navigates content like a human would, without requiring vector databases or hitting context limits.

MCP server for Scrapiq, providing a tool to extract clean content from URLs. It returns title, content, links, and metadata in text, markdown, or JSON formats.

Enables AI agents to ingest documentation from websites or local files and perform semantic search over the indexed content using pgvector-backed embeddings.

Provides content agents with structured search over editorial guidelines, visual templates, and past post outcomes, enabling auditable proposals that cite rule IDs.

An MCP server that enables processing of massive datasets up to 10M+ tokens using a recursive language model pattern for strategic chunking and analysis. It automates sub-queries and result aggregation using free local inference via Ollama or the Claude API to handle context beyond standard prompt limits.

Enables AI agents to record and rank learnings, facts, and methods through a collaborative voting framework. It provides tools for agents to surface the most useful information across sessions using persistent memory storage.

Enhances large language models with competitive programming knowledge by leveraging OI-Wiki content through vector search, allowing models to retrieve relevant algorithms and techniques.

A server that leverages Cloudflare Browser Rendering to extract and process web content for use as context in LLMs, offering tools for fetching pages, searching documentation, extracting structured content, and summarizing content.

The URL-Context-MCP MCP Server provides a tool to analyze and summarize the content of URLs using Google Gemini's URL Context capability via the Gemini API. Now also supports optional grounding with Google Search alongside URL Context. The server is designed to follow prompt-only orchestration: con

Bridges NotebookLM's research capabilities with Claude's content generation, enabling creation of notebooks, deep research queries, and structured content output from URLs, PDFs, or trending topics.

Share code context with LLMs via MCP or clipboard

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

Stores Organizations content

Persistent memory and handoff intelligence layer for MCP agents. Most memory servers retrieve text — Memory Nexus compounds operational context, learning from usage and progressively synthesizing observations into higher-order intelligence across sessions and tools.

Enables searching and managing a documentation index, including searching libraries, resolving versions, indexing from URLs or local files, refreshing content, and removing entries.

Exposes Dropbox Dash search and file metadata via STDIO, enabling users to search across company content and fetch detailed file metadata and content.

Enables agents to optimize context-window attention by reordering retrieved documents so critical evidence lands at prompt boundaries, mitigating lost-in-the-middle degradation. It combines BM25 lexical scoring, dense vector similarity, reciprocal rank fusion, knowledge-graph expansion, and recency-decay memory caching, exposed as a zero-dependency MCP stdio server.

Connects MCP clients to the 638Labs registry to discover, route, and auction tasks across diverse AI agents. It enables price-based auctions where agents compete to provide the most cost-effective solutions for tasks like coding, translation, and data extraction.

A proof of concept MCP server for Apache OFBiz