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Unstructured-IO

Unstructured API MCP Server

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get_workflow_info

Retrieve detailed information about a specific workflow by providing its ID to access configuration, status, and operational data.

Instructions

Get detailed information about a specific workflow.

Args:
    workflow_id: ID of the workflow to get information for

Returns:
    String containing the workflow information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workflow_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'get_workflow_info' tool. It retrieves workflow details from the Unstructured API client and formats them into a readable string output. Registered via @mcp.tool() decorator.
    @mcp.tool()
    async def get_workflow_info(ctx: Context, workflow_id: str) -> str:
        """Get detailed information about a specific workflow.
    
        Args:
            workflow_id: ID of the workflow to get information for
    
        Returns:
            String containing the workflow information
        """
        client = ctx.request_context.lifespan_context.client
    
        response = await client.workflows.get_workflow_async(
            request=GetWorkflowRequest(workflow_id=workflow_id),
        )
    
        info: WorkflowInformation = response.workflow_information
    
        result = ["Workflow Information:"]
        result.append(f"Name: {info.name}")
        result.append(f"ID: {info.id}")
        result.append(f"Status: {info.status.value}")
        if info.workflow_type is None:
            result.append("Type: Undefined")
        else:
            result.append(f"Type: {info.workflow_type.value}")
    
        result.append("\nSources:")
        for source in info.sources:
            result.append(f"  - {source}")
    
        if info.workflow_type and info.workflow_type == WorkflowType.CUSTOM.value:
            result.append("\nWorkflow Nodes:")
            for node in info.workflow_nodes:
                result.append(f"  - {node.name} (Type: {node.type.value}) (Subtype: {node.subtype}):")
                if node.settings:
                    result.append(f"    Settings: {json.dumps(node.settings, indent=8)}")
    
        result.append("\nDestinations:")
        for destination in info.destinations:
            result.append(f"  - {destination}")
    
        result.append("\nSchedule:")
        if info.schedule.crontab_entries:
            for crontab_entry in info.schedule.crontab_entries:
                result.append(f"  - {crontab_entry.cron_expression}")
        else:
            result.append("  - No crontab entry")
    
        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. It mentions returning a string with workflow information but lacks details on permissions, rate limits, error handling, or what 'detailed information' entails. This is insufficient for a tool with no annotation coverage.

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?

The description is front-loaded with the core purpose, followed by clear sections for Args and Returns. Every sentence earns its place, with no wasted words, making it efficient and well-structured.

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?

Given one parameter, no annotations, and an output schema exists (so return values needn't be detailed), the description is mostly complete. It covers the purpose and parameter semantics adequately, though behavioral transparency is lacking.

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 0%, but the description compensates by explaining that 'workflow_id' is the ID of the workflow to get information for. This adds basic meaning beyond the schema's title ('Workflow Id'), though it doesn't specify format 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 verb ('Get detailed information') and resource ('about a specific workflow'), making the purpose evident. However, it does not differentiate from sibling tools like 'get_job_info' or 'get_source_info' beyond the resource type, which is a minor gap.

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?

No guidance is provided on when to use this tool versus alternatives, such as 'list_workflows' for overviews or other 'get_*_info' tools for different resources. The description only states what it does, not when it's appropriate.

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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