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Get Upload Instructions for Local Ontology

get_upload_instructions
Read-onlyIdempotent

Retrieve a curl command to upload a local RDF file to the server and obtain an upload_id, avoiding AI file reading to reduce token usage.

Instructions

Returns the exact curl command to upload a local RDF file to this MCP server and get back an upload_id — without the AI ever reading the file content.

CRITICAL — how to use this tool:

  1. Call this tool with the local file path

  2. Execute the returned curl_command via the Bash tool (do NOT read the file first, do NOT pass its content through the conversation)

  3. Parse the id field from the curl JSON output

  4. Pass the id as upload_id to inspect_local_ontology, query_local_ontology, compare_local_with_remote, or query_uploaded_store

Why this matters: Reading the file and sending its content through the AI conversation wastes tokens and may hit context limits. curl sends the raw bytes directly from the filesystem to the server — the AI never sees the content.

When to use this vs X:

  • use this only when the file is on the client machine and the MCP server cannot read it directly

  • if the server can already read the file, prefer file_path on the local ontology tools

  • if the file is small and you only need a quick summary, inspect_local_ontology with content + format may be enough

HTTP mode only: This workflow requires the MCP server to be running in HTTP mode (MCP_TRANSPORT=http). In stdio mode the HTTP endpoint is not available; use the content parameter of inspect_local_ontology for small files instead.

Docker / reverse-proxy: Set the MCP_PUBLIC_URL env var to the externally reachable base URL (e.g. http://localhost:8080). Without it, the tool falls back to the internal bind address which may be unreachable from outside the container.

Supported formats: .ttl (Turtle), .owl/.rdf (RDF/XML), .nt (N-Triples), .jsonld (JSON-LD), .graphol (Graphol XML)

Uploaded stores expire after 1 hour.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesAbsolute path to the local RDF file to upload
Behavior5/5

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

Annotations indicate read-only and idempotent; description adds context about not reading file content, one-hour expiration, and HTTP mode requirement, with no 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?

Well-structured with headings and lists, but lengthy; every sentence is meaningful given workflow complexity.

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?

Covers all aspects: return value, workflow steps, prerequisites, format support, and expiration, despite no output schema.

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

Parameters3/5

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

One parameter with 100% schema coverage; description adds usage context but no new semantic meaning beyond schema definition.

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?

Description clearly states it returns a curl command to upload a local RDF file, distinguishing it from sibling tools that use upload_id or file_path directly.

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?

Provides step-by-step instructions, when to use vs alternatives (e.g., server-read file, small file), and prerequisites like HTTP mode and Docker setup.

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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