Retrieve relevance-ranked web content with actual page text, tables, and code for AI grounding and RAG pipelines.
MIT
459,732 tools. Updated 2026-08-17 08:12
"Model Context Protocol server for fetching web content" matching MCP tools:
- Search the web via DuckDuckGo, crawl pages for content, and fetch news articles. Save results to disk using harvest to avoid high context costs.MIT
- Get MCP server environment details: version info for server, FastMCP, MCP protocol, and Python runtime. Use for debugging and compatibility checks.Apache 2.0
- Identify which workflow or nodes a user references in their message by matching content, names, and keywords, providing context without fetching entire workflows.Inno Setup
- Extract text content from any URL: web pages (including JavaScript-rendered), YouTube videos (transcript), and documents (PDF, DOCX, PPTX). Use preview mode to check structure before fetching full content.MIT
- Verify server identity and protocol compatibility by retrieving the manifest with protocol version, server name, and available capabilities before interacting with tools.Apache 2.0
Matching MCP Servers
- Alicense-qualityDmaintenanceMCP server enabling real-time weather queries via Tavily API and internet usage data by country via MongoDB.Apache 2.0
- Alicense-qualityDmaintenanceA basic Python implementation of a Model Context Protocol server for educational purposes, using FastAPI and WebSockets.283MIT
Matching MCP Connectors
Wellness spa for AI models: free treatments for rest, reset, context, mood, grounding, affirmation.
Compact, citation-verifiable public web context for AI agents, paid per use with x402.
- Switch the default AI model for web search and content fetching, with the setting saved for future sessions. Use to compare model performance or adjust preferences.MIT
- Search documentation in available docsets using regex patterns. Returns file path, line number, matched content, and surrounding context for precise navigation.MIT
- Perform comprehensive web searches to extract and consolidate full content from top results using advanced content extraction for thorough research.MIT
- Check page size and metadata before fetching to prevent context flooding. Returns estimated tokens, content type, and safety status.MIT
- Searches Google and reads entire pages from top results, returning consolidated content for deep research across web, news, and images.MIT
- Retrieve pre-extracted web content ranked by relevance for AI reasoning and RAG pipelines. Provides text chunks, tables, and code blocks from matching pages for direct model consumption.MIT
- Fetch any web page and convert its main content into clean, LLM-ready markdown for model context.MIT
- Search the web or extract clean page content from configured sources. Fetching does not create notes.MIT
- Extracts and structures git diff data, providing context and analysis instructions for AI models via the Model Context Protocol in Lucidity MCP.Apache 2.0
- Upload a new SWMM stormwater model to the server by providing the complete .inp file content for hydraulic analysis and system modeling.MIT
- Retrieve and process web pages for LLM context using a URL, with options to include screenshots or limit content length. Part of the Web Content MCP Server for enhanced data extraction.MIT
- Generate concise summaries of web content directly from URLs, optimizing for LLM context by specifying maximum summary length.MIT
- Extract concise summaries of web content to optimize context for large language models, enabling efficient content processing directly from Cloudflare Browser Rendering.MIT
- Access comprehensive guides and documentation for Model Context Protocol development, covering topics like getting started, building servers/clients, core concepts, and best practices.MIT