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Showing 5 open source projects for "search"
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Firecrawl MCP Server
Adds powerful web scraping and search to Cursor and Claude
firecrawl-mcp-server is the official MCP integration for Firecrawl that brings high-recall web scraping, crawling, and search into IDEs and agent runtimes. It exposes tools for single-page scrape, multi-URL batch jobs, site discovery, and search enrichment, returning cleaned, structured content suitable for downstream LLM reasoning. The server is designed to run with Firecrawl’s hosted API or self-hosted deployments, making it flexible for enterprise data-governance requirements. ... -
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MCP WebResearch
MCP web research server (give Claude real-time info from the web)
The MCP Web Research Server is a Model Context Protocol server designed to bring real-time web information into AI applications like Claude, facilitating efficient research on any topic. -
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Box MCP Server
A Box model context protocol server to search, read and access files
Box MCP Server is a Model Context Protocol (MCP) server designed to facilitate searching, reading, and accessing files stored on the Box cloud storage platform. It enables seamless integration with Box, allowing for efficient file management and retrieval through MCP-compatible clients. -
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The Web MCP
A powerful Model Context Protocol (MCP) server
Bright Data’s Web MCP server gives AI assistants robust, real-time web capabilities through an MCP interface designed to avoid blocks, rate limits, and CAPTCHAs. It presents search, crawl, navigate, and extraction tools that agents can call directly, replacing brittle scraping prompts with typed operations. The README markets it as a “gateway” to the live web so assistants don’t fall back to stale training data. Bright Data also advertises a getting-started tier with a free monthly allotment, plus options for remote or self-hosted operation depending on governance needs. ... -
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5
Deep Research
Use any LLMs (Large Language Models) for Deep Research
Deep Research is a local-first research agent that orchestrates multiple LLMs to generate in-depth reports in minutes. It combines “thinking” and “task” model roles with live internet access to plan, search, read, and synthesize findings into structured outputs. The project emphasizes privacy: processing and storage happen locally, avoiding server-side retention of your queries and notes. A simple web UI lets you enter topics and configure models, while the backend streams progress as sources are fetched and arguments are weighed. It offers MCP server support and SSE APIs, so IDEs and agent clients can drive the same workflow programmatically. ...
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