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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.
    1
    7 npm
    2
    MIT
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    Enables AI agents to perform web search, extraction, and research across multiple provider backends with persistent multi-key rotation and auditable routing. Supports MCP, CLI, and Agent Skill entry points.
    MIT
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    Enables parallel research across multiple cheap AI worker models, splitting a question into sub-questions and synthesizing one sourced answer with references.
    MIT
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    An MCP server that exposes an Agno agent with Google Gemini reasoning and Serper web search, enabling MCP-compatible clients like Claude Desktop to perform agent-driven web searches and receive synthesized answers.
    1
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    MIT
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    An MCP server that enables web search capabilities using OpenAI's o3 model, allowing AI assistants to perform text-based web searches and return AI-powered results.
    1
    219 npm
    287
    MIT
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    A Model Context Protocol server that provides Google Jobs search capabilities through SerpAPI integration, featuring multi-language support, flexible search parameters, and rich job details.
    1
    6 npm
    22
    MIT
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    A comprehensive Google Ads API integration for AI assistants through the Model Context Protocol. This server enables Claude AI and other MCP-compatible clients to manage Google Ads campaigns, analyze performance, and execute GAQL queries with natural language commands.
    76
    MIT
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    Enables web search for the pi coding agent using z.ai GLM native search with a DuckDuckGo fallback.
    3,283 npm
    MIT
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    Enables clients of tool-heavy MCP aggregators to find and use upstream tools on demand through four fixed bridge tools (search, describe, call, refresh), cutting per-turn tool context from ~180k tokens to ~2–3k. It merges multiple upstream servers behind sticky sessions and a local lexical BM25 index, so only the schemas actually needed are retrieved.
    6
    MIT
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    Replaces DSH's built-in web_search with pluggable MCP search backends such as Tavily, Brave, Exa, Perplexity, DuckDuckGo, or custom HTTP/stdio servers. Users configure providers in the settings UI with secure credential references, while the model keeps calling the native web_search tool.
    MIT
  • F
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    Enables real-time web search with source citations by leveraging Perplexity AI's Sonar models through SAP AI Core. It integrates with Claude Code to provide deep analysis, reasoning, and up-to-date information from the web.
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