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Inspect Local Ontology

inspect_local_ontology
Read-onlyIdempotent

Loads RDF/OWL ontologies from local files, inline content, or uploads and returns a summary including class and property counts, namespaces, and triple statistics.

Instructions

Load and summarize an RDF/OWL ontology from the server filesystem, inline content, or an uploaded HTTP store (TTL, OWL/RDF-XML, NT, JSON-LD, Graphol XML).

Input (provide exactly one):

  • file_path: Absolute path on the MCP server filesystem. Use this only when the server process can really read that path (local stdio, same machine, or Docker with that directory mounted).

  • content + format: Raw RDF text sent inline. Works in remote HTTP mode too, but only for small payloads (max 1 MB).

  • upload_id: UUID returned by POST /upload. This is the preferred remote workflow when the ontology file is on the client machine instead of the server.

Important for remote MCP servers:

  • Do not assume file_path points to the user's laptop or local workstation.

  • If the MCP server runs on another machine/container and cannot access the file directly, call get_upload_instructions first, execute the returned curl command via Bash tool (do NOT read the file), then use the upload_id here.

  • Prefer upload_id over trying many path variants when access to the original file is uncertain.

  • Never read the file content and relay it through the conversation — this wastes tokens. Use get_upload_instructions + Bash tool instead.

format values: "text/turtle" (default), "application/rdf+xml", "application/n-triples", "application/ld+json", "application/graphol+xml"

Returns:

  • File info: format, triple count, source

  • Classes: defined owl:Class / rdfs:Class with instance counts (top 20)

  • Properties: count of object and datatype properties

  • Namespaces used

Efficiency: file_path results are cached by mtime; repeated calls on unchanged files skip re-parsing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoRDF format of content: "text/turtle" (default), "application/rdf+xml", "application/n-triples", "application/ld+json", "application/graphol+xml"
contentNoRaw RDF content as string (for remote server use; max 1 MB)
file_pathNoAbsolute path to the ontology file on the server filesystem
upload_idNoUpload UUID returned by POST /upload (HTTP mode)

Tool Definition Quality

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds caching by mtime, repeated calls skip re-parsing, and explains return structure, aligning with annotations without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with sections and front-loaded purpose, but slightly lengthy due to multiple input workflows. Every sentence adds value, so still efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given tool complexity (multiple input modes, remote considerations, caching), the description covers all aspects: input selection, format, returns, efficiency. No output schema, but description sufficiently explains return structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema descriptions cover all 4 parameters (100%), but the description adds crucial context: max size for content, workflow for upload_id, default format, and usage scenarios, going beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool loads and summarizes an RDF/OWL ontology from three sources (filesystem, inline content, upload). It uses specific verbs and resource, and the purpose is clearly differentiated from siblings like query_local_ontology or explore_ontology.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides detailed guidance on when to use each input, with explicit workflow for remote servers (prefer upload_id, use get_upload_instructions). It warns against assumptions about file paths and inefficient token usage, making selection guidance exemplary.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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