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Related Servers

Alternatives to open-ontologies

  • A
    license
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    quality
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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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  • A
    license
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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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Related Servers

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    An MCP server that enables AI-powered exploration of RDF data and SPARQL querying via RDF4J. It provides tools for executing queries, searching knowledge graph resources, and retrieving schema summaries.
    13
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  • A
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    MCP server exposing SPARQL query functionalities for LLMs, enabling query execution, validation, and graph exploration across SPARQL endpoints.
    7
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  • F
    license
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    A Knowledge Graph MCP server optimized for LLM context efficiency through compact JSON and SQLite persistence. It enables full graph management including node/edge CRUD operations, full-text search, and subgraph traversal.
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  • A
    license
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    MCP server for a self-hostable typed knowledge graph, giving AI agents durable structured memory with typed nodes, links, and flexible payloads. Enables agents to bootstrap, manage, and evolve their ontology via MCP tools.
    3,288 npm
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TDQS

A3.6/5.0

Scored across 42 tools

Disambiguation5/5

All tools have clearly distinct purposes with detailed descriptions. The variety of operations (loading, reasoning, alignment, validation, feedback) are well-separated, and even similar-sounding tools like onto_validate, onto_shacl, and onto_validate_clinical are differentiated by their specific functions.

Naming Consistency5/5

All tools follow a consistent 'onto_' prefix with snake_case naming. Verbs are clear and descriptive (e.g., onto_load, onto_reason, onto_align_feedback). There is no mixing of conventions, making the toolset predictable and easy to navigate.

Tool Count4/5

42 tools is on the high side but justified by the comprehensive scope of ontology management (loading, reasoning, alignment, validation, versioning, monitoring). Some tools could be merged (e.g., feedback variants), but overall the count reflects the server's ambitious feature set.

Completeness3/5

The toolset covers many core ontology operations (load, reason, validate, align, version) but lacks fine-grained editing capabilities such as adding/removing individual triples or listing entities directly. The presence of feedback and monitoring tools suggests a mature system, yet basic CRUD operations are missing.

Maintenance

ActivityActive
ResponsivenessResponsive