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Unstructured-IO

Unstructured API MCP Server

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get_job_info

Retrieve detailed information about a specific job by providing its ID to access status, progress, and related data from the Unstructured API.

Instructions

Get detailed information about a specific job.

Args:
    job_id: ID of the job to get information for

Returns:
    String containing the job information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'get_job_info' tool. It is decorated with @mcp.tool(), which registers it as an MCP tool. The function fetches job information from the Unstructured API client using the provided job_id and formats it into a readable string.
    @mcp.tool()
    async def get_job_info(ctx: Context, job_id: str) -> str:
        """Get detailed information about a specific job.
    
        Args:
            job_id: ID of the job to get information for
    
        Returns:
            String containing the job information
        """
        client = ctx.request_context.lifespan_context.client
    
        response = await client.jobs.get_job_async(
            request=GetJobRequest(job_id=job_id),
        )
    
        info = response.job_information
    
        result = ["Job Information:"]
        result.append(f"Created at: {info.created_at}")
        result.append(f"ID: {info.id}")
        result.append(f"Status: {info.status}")
        result.append(f"Workflow name: {info.workflow_name}")
        result.append(f"Workflow id: {info.workflow_id}")
        result.append(f"Runtime: {info.runtime}")
        result.append(f"Raw result: {json.dumps(json.loads(info.json()), indent=2)}")
    
        return "\n".join(result)
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states this is a read operation ('Get'), but doesn't mention any behavioral traits like authentication requirements, rate limits, error conditions, or what 'detailed information' entails. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

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 appropriately concise with three brief sentences that are front-loaded (purpose first, then args, then returns). Each sentence serves a clear purpose, though the 'Returns' section could be more informative given the output schema exists.

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

Completeness3/5

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

Given the tool's moderate complexity (single parameter read operation), no annotations, and the presence of an output schema, the description is minimally adequate. It covers the basic purpose and parameter but lacks behavioral context and usage guidance. The output schema reduces the need to explain return values, but more completeness would include when to use this versus sibling tools.

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?

The description adds minimal semantic context for the single parameter 'job_id' by stating it's 'ID of the job to get information for', which slightly clarifies its purpose beyond the schema's basic 'Job Id' title. With 0% schema description coverage and only one parameter, this meets the baseline expectation but doesn't provide rich additional context like format examples or constraints.

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

Purpose4/5

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('detailed information about a specific job'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_jobs' or 'check_crawlhtml_status', which might provide related job information in different contexts.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'list_jobs' (for listing multiple jobs) and various 'check_status' tools, there's no indication of whether this is for general job details, status checks, or other purposes, leaving the agent to infer 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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