Lightweight browser automation server for AI agents, enabling fast (10-25ms per action), structured observations and semantic selectors with zero token overhead.
Enables web content retrieval and semantic search capabilities through the Jina AI API. Provides tools to fetch content from URLs and perform intelligent web searches with natural language queries.
Enables agents to control a real Chromium browser with semantic tools, providing compact observations and outcome-verified actions for web interaction tasks.
MCP server that transforms Gurunavi into a browser-driven semantic proxy, providing restaurant search, details, and reservation management through normalized interfaces with safety controls.
Token-optimized Playwright MCP server that reduces context window usage by 73.8% by grouping 22 tools into 6 semantic operations, enabling AI assistants to control browsers with minimal token overhead.
Turn your Chrome browser into an AI-powered automation tool, enabling browser control, content analysis, and semantic search via Model Context Protocol.
Provides web content extraction, search capabilities (web, arXiv, SSRN, images), semantic deduplication, and reranking through Jina AI's Reader, Embeddings, and Reranker APIs.
A semantic terminal browser that renders web pages as structured numbered elements for LLM agents via MCP, enabling agents to navigate, interact, and extract data from any website.
Provides web crawling and RAG capabilities for AI agents, enabling scraping of websites, storing content in a vector database (Supabase), and performing semantic search over crawled data.
MCP server for local semantic search over web content, enabling AI agents to ingest, index, and query pages with hybrid retrieval and token budget control.
Semantic browser automation MCP server that lets AI agents control a browser using natural language, handling navigation, form filling, data extraction, and more without CSS selectors.
Provides access to Jina AI's Search Foundation APIs for embeddings, web search, content extraction, reranking, classification, and semantic text segmentation.
Crawls documentation websites and provides semantic search capabilities over the content through vector embeddings, enabling natural language queries of technical documentation.
Enables AI assistants to search, filter, and extract job listings from LinkedIn using an automated headless browser with semantic AI filtering and deduplication.
Web crawling and RAG implementation that enables AI agents to scrape websites and perform semantic search over the crawled content, storing everything in Supabase for persistent knowledge retrieval.
Provides access to LangSearch's Web Search and Semantic Rerank APIs for AI assistants. It enables web searching with advanced filtering and reranking of documents based on semantic relevance.