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"Exploring Deep Search Techniques or Tools" matching MCP servers:

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    MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.
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    Enables intelligent code analysis and search across repositories using the CodeRank algorithm (inspired by PageRank) to identify critical modules, trace dependencies, find code hotspots, and perform context-aware keyword searches with importance-ranked results.
    21
    32
    Apache 2.0
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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.
    6
    52
    MIT
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    An MCP server that provides autonomous, multi-source web research capabilities for AI agents. It delivers comprehensive, validated information through deep research tools while maintaining security and compatibility with various LLM providers.
    MIT
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    MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution
    21
    MIT
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    A multi-agent research system that decomposes complex queries into targeted sub-questions, searches the web in parallel, scores source credibility, and synthesizes findings into structured markdown reports.
    1
    1
    MIT
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    An MCP server that provides a structured, persistent scratchpad for hard reasoning, with staged reasoning and self-critique, built for local models.
    25
    MIT
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    This is a Model Context Protocol (MCP) server adaptation of LangChain Ollama Deep Researcher. It provides the deep research capabilities as MCP tools that can be used within the model context protocol ecosystem, allowing AI assistants to perform in-depth research on topics (locally) via Ollama
    3
    16
    MIT
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    MCP server for compressing AI embeddings by 5-7x using TurboQuant (PolarQuant + QJL), with tools to compress, decompress, estimate savings, and embed+compress vectors.
    MIT
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    MCP server for searching files on macOS by name or content using semantic and lexical search, providing file paths and line numbers for agents to read from.
    MIT
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    A passive MCP server that exposes a toolbox of executable tools (shell, network, HTTP, AI search, SSH, S3 file operations) to autonomous agents via Streamable HTTP, with strong security features including Docker sandboxing and WAF.
    2
    Apache 2.0