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    Integrates Dify's external knowledge base API with the Model Context Protocol to enable AI agents to retrieve and query relevant information. It supports relevance scoring, metadata filtering, and flexible configuration through environment variables or command-line arguments.
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    MIT
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    MCP server giving AI agents real-time web search, page scraping, company intelligence, email discovery, local lead generation, and a persistent knowledge graph. Pay only for what you use, no subscriptions.
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    MIT
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    MemOS (Memory Operating System) is a memory management operating system designed for AI applications. Its goal is: to enable your AI system to have long-term memory like a human, not only remembering what users have said but also actively invoking, updating, and scheduling these memories.
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    Apache 2.0
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    An AI conversation management layer that enables creating chat sessions, persisting message history to GitHub, and performing semantic searches over past interactions. It supports multi-turn threading and context injection to integrate external memory sources into Claude conversations.
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    Shared research cache for AI agents. Caches web research across sessions and users - hit means instant answer from verified sources, miss means your research saves the next dev's tokens. Semantic search with freshness tracking, gap detection, and real-time token measurement via JSONL. Free, open source.
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    AGPL 3.0
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    A Context-as-a-Service MCP server that maintains structured, graph-based context for Shopify apps by extracting and summarizing data from web sources and help centers. It enables multi-agent systems to retrieve isolated, provenance-backed context slices or starter bundles via push and pull mechanisms.
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    A Model Context Protocol server that enables AI models to interact with SourceSync.ai's knowledge management platform for managing documents, ingesting content from various sources, and performing semantic searches.
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    ISC