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Query Uploaded Store

query_uploaded_store
Read-onlyIdempotent

Run SPARQL SELECT queries against a temporary ontology store uploaded via HTTP. Use the upload ID to retrieve specific data from the store.

Instructions

Execute a SPARQL SELECT query against a temporary ontology store created via HTTP upload.

Workflow (HTTP mode only):

  1. Call get_upload_instructions with the local file path → get the curl command

  2. Execute the curl command via Bash tool (file bytes go directly to the server, no AI token consumption)

  3. Parse the id from the curl response

  4. Use id here to run SPARQL queries, OR pass it as upload_id to inspect_local_ontology, query_local_ontology, compare_local_with_remote

When to use this workflow:

  • The MCP server is remote, containerized, or otherwise cannot read the user's local filesystem.

  • A previous file_path attempt failed because the path only exists on the client machine.

  • You want to send raw file bytes directly without consuming model tokens.

When to use this vs X:

  • prefer query_local_ontology with upload_id for the main MCP workflow

  • use this only if you already have the upload store id and explicitly want to query that temporary store directly

Deprecated direction: this is an upload-specific shortcut; for new agent flows prefer query_local_ontology with upload_id

Supported Content-Types for upload: text/turtle, application/rdf+xml, application/n-triples, application/ld+json, application/graphol+xml

Notes:

  • Uploaded stores are kept for 1 hour then evicted

  • Standard prefixes (rdf/rdfs/owl/skos/dct/xsd/dcat/foaf/clv/cpv/l0/sm) are auto-injected

  • The same store is also queryable directly via GET /sparql/<id>?query=...

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUpload UUID returned by POST /upload
queryYesSPARQL SELECT query to execute against the uploaded store

Tool Definition Quality

A4.7/5.0
Behavior5/5

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

Builds on annotations (readOnly, idempotent, non-destructive) by adding key behavioral facts: stores evicted after 1 hour, standard prefixes auto-injected, and alternative direct endpoint access. No contradiction with annotations.

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 clear sections (summary, workflow, when-to-use, alternatives, notes). Front-loaded with purpose. Slightly verbose due to workflow details that could be external, but every sentence is informative and earns its place.

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

Completeness4/5

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

Very complete for a complex tool: explains prerequisite workflow, supported content types, eviction policy, and prefix injection. Lacks specification of the output format (e.g., SPARQL results JSON), but this is somewhat implied by the nature of a SPARQL query tool.

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

Parameters4/5

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

Schema already has 100% description coverage for both parameters (id and query). The description adds context about where the id comes from (workflow step 3) and that query is a SPARQL SELECT, but does not add syntax or format details beyond the 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 clearly states it executes SPARQL SELECT queries against a temporary ontology store created via HTTP upload, specifying both the resource (temporary store) and action (querying). It distinguishes from siblings like query_local_ontology and query_sparql by emphasizing the upload workflow.

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 explicit step-by-step workflow, conditions for when to use (HTTP mode only, remote server scenario), and clear alternatives (prefer query_local_ontology with upload_id). Also includes deprecation note guiding toward newer flows.

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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