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docuprox-mcp

docuprox-mcp

Official
by docuprox
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TypeScript
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job_results

Fetch extracted results from a completed document processing job using a job ID, with optional JSON or CSV format selection.

Instructions

Fetch the extracted results of a completed asynchronous DocuProx processing job. Requires a valid job_id and optionally a format ('json' or 'csv').

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "job_id": "<job_id>"
    },
    "name": "job_results"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYesUUID of the job.
result_formatNoFormat of the results ('json' or 'csv'). Defaults to 'json'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does reasonably well: it states that this is a retrieval operation for results of a completed job. It does not discuss failure behavior or whether results are retained, but for a simple fetch operation the core behavior is transparent enough.

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

Conciseness5/5

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

One sentence with no filler. The key action, resource, prerequisite, and optional format are all front-loaded efficiently.

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?

For a low-complexity read tool with fully documented parameters, the description covers the essential prerequisites and result format. It lacks detail about the return payload, but since there is no output schema and the tool name itself communicates 'results', this is a minor gap.

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?

Schema description coverage is 100%, so the input schema already documents job_id and result_format. The description adds minor value by restating the format options and the optionality in natural language, but it does not introduce meaning 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 uses a specific verb ('Fetch') with a clear resource ('extracted results of a completed asynchronous DocuProx processing job'). This distinguishes it from siblings like job_status, which would report job state, and process_job, which would start a job.

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

Usage Guidelines4/5

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

It clearly conveys that the tool is for completed jobs and requires a job_id, giving an agent the core context for when to call it. It does not explicitly name alternatives or state when not to use it, but the 'completed' prerequisite provides solid usage context.

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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