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"Learning NestJS Framework Knowledge" matching MCP servers:

  • A
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    quality
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    MCP server for managing notes with CRUD tools. It uses the same notes service as the GraphQL API, enabling natural language interaction with notes.
    47
    MIT
  • F
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    quality
    D
    maintenance
    A robust server-side application that implements Model Context Protocol (MCP) for file operations, providing authentication and modular REST APIs for managing files, users, and posts.
  • F
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    quality
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    Enables AI assistants like Claude to interact with MongoDB databases through standardized MCP tools. Supports full CRUD operations, aggregations, and natural language queries with Clean Architecture and dual transport modes (STDIO/HTTP).
  • F
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    A comprehensive framework for building remote MCP servers on Cloudflare Workers featuring OAuth 2.1 authentication, PostgreSQL integration, and Stripe-powered paid tools. It enables developers to create scalable, platform-agnostic MCP tools with support for user registration and subscription-based functionality.
    127
  • A
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    quality
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    A persistent memory server that implements a local knowledge graph using the Kuzu embedded database to store entities, relationships, and observations. It enables AI models to maintain structured long-term context through searchable nodes and comprehensive tag-based organization.
    10
    MIT
  • A
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    quality
    B
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    An embedded knowledge graph in one SQLite file, exposing a MCP server for agents to read and write entities and relationships with full audit trail and time travel.
    1
    MIT
  • F
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    quality
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    A TypeScript MCP server for managing persistent knowledge graphs with entities, directional relations, and time-based observations. It enables users to create, search, and track structured information with built-in concurrency control and JSON file storage.
  • A
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    quality
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    Agentic RAG Knowledge Assistant is a secure, tenant-isolated MCP server built with FastAPI, PostgreSQL, and pgvector that enables document ingestion, semantic retrieval, and vector search over PDF, DOCX, and text files through authenticated MCP tools.
    MIT
  • A
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    quality
    C
    maintenance
    Enables LLMs to manage file-based knowledge bases with dual storage (Markdown + SQLite). Supports creating, searching, and organizing articles across multiple knowledge bases with full-text search capabilities.
    14
    3
    MIT
  • F
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    quality
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    maintenance
    MCP server for AI-powered roadside assistance case management, exposing SQLite-backed tools for querying case counts, statuses, and summaries through natural language via Gemini function calling.
  • F
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    Enables storage and retrieval of knowledge in a graph database format, allowing users to create, update, search, and delete entities and relationships in a Neo4j-powered knowledge graph through natural language.
    5