"Information about 'fetch' or related resources" matching MCP servers:

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

Fetch URLs and return clean, LLM-ready markdown with metadata and layered prompt injection defense. Configurable timeouts, word limits, JS rendering, and link extraction. All-in-one MCP server + CLI.

A Model Context Protocol server that intelligently fetches and processes web content, transforming websites and documentation into clean, structured markdown with nested URL crawling capabilities.

A powerful MCP server for fetching and transforming web content into various formats (HTML, JSON, Markdown, Plain Text) with ease.

Provides web content fetching capabilities using Playwright browser automation, enabling LLMs to retrieve and process JavaScript-rendered content from web pages and convert HTML to markdown for easier consumption.

Enables LLMs to autonomously retrieve and explore web content by fetching pages and recursively following links to a specified depth, particularly useful for learning about topics from documentation.

Enables retrieval and processing of web page content for LLMs by converting HTML to markdown, with support for content truncation and pagination.

Fetches web page content, converts it to Markdown, and optionally processes it with a local LLM. Returns structured data in TOON format optimized for agent consumption.

Fetches web content and returns relevant chunks using RAG with semantic chunking, query-based scoring, and LexRank, supporting PDFs and 50+ languages.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

An MCP server that fetches web pages and extracts clean, AI-friendly Markdown content using Mozilla Readability. It provides secure web access for LLMs with built-in SSRF protection and automated content cleaning for improved context retrieval and summarization.

MCP server for searching French and European law, providing natural language access to jurisprudence, consolidated legal texts, and related legal information via tools like search_decisions and search_legal_texts.

Exposes hybrid retrieval (dense embeddings + BM25 + RRF) and document operations (search, fetch, rerank) as MCP tools, using Qdrant and OpenAI embeddings for local or server mode.

Lets AI agents search and read a folder of Markdown documentation at query time, exposing heading-level search, whole-page or section retrieval, and page listing as tools and resources over stdio or Streamable HTTP. Can run as a CLI, a hosted endpoint, or a library inside an existing Node or Next.js site.

Give your AI agents access to 8,500+ community curated awesome lists with over 1 million curated resources.

Enables AI assistants to search and ask questions about documents stored in AnythingLLM workspaces through MCP tools.

Enables AI assistants to search and retrieve transcripts from the Entra.Chat podcast about Microsoft Entra ID, with timestamped YouTube links and guest information.

Enables AI agents to persist facts with tags, sources, and importance in a local SQLite database, retrieve them through hybrid BM25 plus embedding search weighted by retention decay, link or supersede related entries, and review everything in a read-only visual dashboard showing the memory graph and timeline.

Fetch any web page as clean Markdown or plain text, split it into heading-aware, token-bounded RAG chunks, convert raw HTML, and read page metadata. Uses the Web2MD API on RapidAPI with your own key (free BASIC plan).

An AI-powered documentation navigator that enables intelligent search, summarization, and exploration of SUSE, Rancher, and related open-source documentation using local or cloud AI models.

Enables searching and retrieving content from Grokipedia, with tools for page lookup, citations, sections, and related pages.

An MCP server that retrieves contextual information from company resources and surfaces it to coding agents as rules, reasoning, skills, and commands.

Enables LLM agents to search academic literature, explore citation graphs, discover related papers, and export BibTeX using arXiv and Semantic Scholar, with prompts for evidence-grounded related-work summaries.

Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.

Enables AI agents to record, recall, correct, and forget evidence-backed factual claims with temporal history, while explaining whether remembered information is current, historical, or contested.

A Model Context Protocol server that allows AI agents to perform WHOIS lookups, enabling users to directly ask the AI about domain availability, ownership, registration details, and other domain information.

Enables MCP clients to retrieve authoritative AI Square documentation, API references, SDK examples, guides, and troubleshooting information through citation-safe hybrid search and static resources.

Enables agents to query a self-hosted, locally indexed web corpus through MCP tools for keyword, neural, or hybrid search, to fetch clean text from already-indexed URLs, and to discover pages similar to an indexed URL.

Provides LLMs with specialized knowledge about fountain pen inks, enabling intelligent ink search, color matching, and recommendations through various tools.

A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.