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    Enables AI agents to inspect ontology schemas, search typed objects, and execute read-only SPARQL queries against an RDF triple store.
    3
    MIT
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    Reference implementation of the Operational Ontology pattern: MCP tools are generated from a typed business domain model (objects, links, actions) — one tool per query shape and per action, deliberately no raw SQL tool. Writes pass business-rule preconditions, are audited, and write back to the systems of record; refusals are machine-readable. Ships with a demo orders ontology spanning two legacy
    34
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    MIT
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    An MCP server that uses an OWL/SHACL/SKOS knowledge graph to interpret login-diagnosis prompts and return JSON-LD descriptors, guiding Copilot agents to the appropriate SQL Server and MongoDB queries and enabling New Relic escalation when needed.
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    Enables AI assistants to navigate and populate complex ontologies by transforming unstructured data into structured, SHACL-validated knowledge graphs. It features semantic hybrid search and proactive schema guidance to help users build deeply linked, reasoning-ready data.
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    Enables AI agents to interact with ontology knowledge graphs via MCP SSE, supporting ontology and instance CRUD, relationship traversal, dynamic function registration, role-based tool permissions, and graph visualization.
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    A Model Context Protocol (MCP) server that connects GraphDB's SPARQL endpoints and Ollama models to Claude, enabling Claude to query and manipulate ontology data while leveraging various AI models.
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    3
    MIT
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    Enables governed interaction with synthetic people data through MCP tools, providing per-caller scoped access, semantic-layer metrics, and read-only SQL with authorization checks.
    MIT
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    Universal database copilot for diagnostics, operations, and performance analysis via MCP and CLI.
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    Persistent memory management for AI assistants like Claude, enabling creation, search, and retrieval of memories with tagging and triggers.
    10
    MIT
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    Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.
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    MIT
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    A Model Context Protocol (MCP) server for developing Django applications. It exposes Django project information through MCP tools, enabling AI assistants to better understand and interact with Django codebases.
    705 PyPI
    112
    MIT
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    A production-style MCP server exposing six business tools (web search, database, CRM, email, calendar, analytics) to AI clients via a secure, authenticated interface, with mock mode and a reference agent client.
    MIT
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    Enables AI-powered interaction with Metabase instances and PostgreSQL databases through natural language. Creates models, SQL queries, metrics, and dashboards using both Metabase API and direct database connections.
    36 npm
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    Apache 2.0
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    Enables a unified AI assistant that combines document retrieval (RAG), database queries via MCP tools, and web search, allowing users to ask complex questions and receive answers from multiple enterprise sources.
    MIT
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    Enables AI assistants to securely triage SuperOffice CRM support cases by retrieving tickets, running database diagnostics, searching knowledge bases, and orchestrating cross-system incident investigations.
    MIT