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"A search for information about thinking or related concepts" matching MCP servers:

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    Enhances AI model capabilities with structured, retrieval-augmented thinking processes that enable dynamic thought chains, parallel exploration paths, and recursive refinement cycles for improved reasoning.
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    MIT
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    An advanced MCP server that implements sophisticated sequential thinking using a coordinated team of specialized AI agents (Planner, Researcher, Analyzer, Critic, Synthesizer) to deeply analyze problems and provide high-quality, structured reasoning.
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    Federated, local-first search for AI agents: one query fans across transcripts, files, a knowledge graph, a vector store, the live web, and YouTube, fused by trust-weighted RRF into one ranked answer. Five modes (grep/lexical/semantic/hybrid/rerank), runs entirely on your machine over MCP.
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    Apache 2.0
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    Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.
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    MIT
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    Enables AI-powered web searches using Google's Gemini 2.5 models with Google Search Grounding. Supports multiple Gemini models (Flash, Flash-Lite, Pro) with configurable thinking budget and web search capabilities.
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    MIT
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    MCP search and evidence tool for AI agents. Rewrites queries, zooms into source domains, and returns sourced answers with metrics.
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    MIT
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    Semantic, on-demand skill retrieval for Claude Code that saves tokens and improves skill discovery by replacing the native skill listing with vector embedding search.
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    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 self-hosted, MCP-native web-search backend for AI agents that provides meta-search, clean extraction, RAG with citations, and GitHub project selection.
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    MIT
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    Enables web search and AI-summarized answers via an x402-gated gateway, with options for structured results or enriched summaries, accessible as an MCP server.
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    Enables semantic search across conversation archives via MCP, allowing AI clients to retrieve relevant past conversations using vector embeddings and text fallback.
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    ISC
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    A Model Context Protocol server that uses Google Vertex AI and Gemini 3.5 Flash to perform deep research with high thinking capability and live Google Search grounding, enabling intelligent, multi-source research via a single tool.
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    Enables semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.
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    A local-first MCP server that enables semantic search over PDF and DOCX documents using structure-aware parsing and vector storage. It allows users to query their local knowledge base through Claude Code without cloud dependencies or GPU requirements.