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"Hybrid Memory Models Combining Relational, Graph, and RAG Approaches" matching MCP servers:

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    Helps construct and validate Microsoft Graph REST API calls with on-demand tool loading, providing request details, required permissions, and code examples for categories like users, files, mail, calendar, groups, notes, tasks, sites, and subscriptions.
    Last updated
    15
    MIT
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    Enables querying Confluence or Kubernetes documentation through hybrid search and an agentic RAG pipeline, returning structured answers with citations.
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    Apache 2.0
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    Transforms static gemini-cli documentation into a queryable RAG service, enabling developers to ask questions about Gemini CLI in natural language and receive instant, accurate answers based on the official documentation directly within their workflow.
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    8
    MIT
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    A Model Context Protocol (MCP) server with Retrieval-Augmented Generation (RAG) for answering questions about imaginary SuperNova documentation. Enables semantic search over documentation using HuggingFace embeddings.
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    1
    MIT
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    A local MCP server that accumulates the business-domain knowledge of a software project — flows, integrations, decisions, nuances — and makes it available to any MCP-compatible agent (Claude Code, Cursor, Copilot, Gemini, OpenCode). The goal is to capture the why behind the code: the stuff a new developer would need six months from now to understand why a thing is built the way it is. The what is
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    4
    Apache 2.0
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    An MCP server that enables users to query Kedro framework documentation using retrieval-augmented generation. It builds a local knowledge base from documentation files to help users navigate and apply Kedro's data science pipeline framework.
    Last updated
  • F
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    This MCP server provides a deterministic index of the First Principles Framework (FPF) spec, enabling agents to query patterns, routes, and relations without vector databases.
    Last updated
    6
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    A server for managing project documentation and context across Claude AI sessions through global and branch-specific memory banks, enabling consistent knowledge management with structured JSON document storage.
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    41
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    MIT
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    Enables AI assistants to fetch, index, and perform semantic RAG-based searches on API documentation from various sources. It provides tools for hybrid search and collection management, allowing users to access up-to-date documentation from projects like Gemini and FastMCP.
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    Provides AI agents with instant access to official Apple developer documentation, Swift programming guides, design guidelines, and Apple Developer YouTube content including WWDC sessions. Uses advanced RAG technology with semantic search and AI reranking to deliver accurate, contextual answers for Apple platform development.
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    7
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    Provides AI agents with instant access to official Apple developer documentation, Swift docs, design guidelines, and Apple Developer YouTube content through advanced semantic and hybrid search capabilities. Features AI-powered reranking for accurate retrieval of Apple platform knowledge including iOS, macOS, watchOS, tvOS, and visionOS development resources.
    Last updated
    5