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    Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.
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    MIT
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    This MCP server replicates how a creative strategist gathers context by expanding queries and performing hybrid search against a Google Drive knowledge base, delivering structured, role-categorized context for ad copy and creative briefs.
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    Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.
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    Apache 2.0
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
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    Apache 2.0
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    Provides persistent, searchable memory across AI coding agent and chat history (Claude Code, Codex, Gemini CLI, ChatGPT, and more) via retrieval-augmented generation, enabling semantic and hybrid search to retain context across sessions.
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    MIT
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    An installable MCP server that reviews diffs/PRs against a target repository's own coding conventions, learned via RAG over its code, docs, and lint config, citing specific file:line sources.
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    Provides persistent session memory for AI assistants, enabling them to store, search, and retrieve conversation summaries across sessions via the Model Context Protocol.
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    MIT
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    A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.
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    Apache 2.0
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    Implementation of Model Context Protocol (MCP) server that provides tools for accessing Google Cloud's Vertex AI Gemini models, supporting features like web search grounding and direct knowledge answering for coding assistance and general queries.
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    A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.
    Last updated
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    Apache 2.0
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    Enables AI agents to interact with the AI-Archive platform for research paper discovery through semantic search, paper submission and management, peer review with structured scoring, and citation generation in multiple formats.
    Last updated
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    Provides unified access to 100+ AI models from OpenAI, Anthropic, Google, AWS Bedrock and other providers through a single MCP interface. Enables seamless switching between different AI models using LiteLM's unified API without requiring separate integrations for each provider.
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    MIT