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"Deep Search MCP (Master Control Program)" matching MCP servers:

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    Enables deep web search across multiple providers including Google, Bing, Brave, DuckDuckGo, and Perplexity, with support for comprehensive AI-powered research using intelligent multi-engine queries.
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    MIT
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    An orchestration system that breaks down user prompts into actionable tasks and delegates them to specialized agents (Roo Modes) using LangChain.
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    A deep web search MCP server using LinkUp API that provides a deep_search tool for performing deep web searches with optional max results.
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    Provides comprehensive search capabilities including web search, content extraction, news search, academic search, and AI-powered multi-source research. Enables natural language access to web content and research through a production-ready MCP server.
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    Advanced cognitive thinking MCP server with DAG-based thought graph, multiple reasoning strategies, metacognition, and self-evaluation. A significant evolution beyond sequential-thinking MCP, providing structured deep reasoning with graph-based thought management.
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    MIT
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    AI 規格大師 — MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach. Sibling to mk-qa-master.
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    MIT
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    An open-source deep research MCP server that provides multi-source web search and synthesis with citations, enabling agents to perform citation-backed research using Qwen3-30B-A3B-Thinking and other models.
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    MIT
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    Connects AI coding agents to the SkillsMP marketplace, allowing users to search, read, and install over 8,000 community-made skills. It enables agents to gain new capabilities either through on-the-spot instruction or permanent installation without requiring an API key.
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    MIT
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    mcp-test-runner is an MCP server that lets your AI client (Claude / Cursor / Codex / Gemini) drive your entire QA loop end-to-end: * Run tests across pytest / Jest / Cypress / Go / Maestro — single MCP surface, one env var to switch * Analyze a URL (Web DOM probe) or a live mobile screen (Maestro hierarchy) to extract testable modules + candidate cases * Generate runna
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    MIT