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intruder-mcp

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get_scanner_output

Retrieve the scanner output for a specific occurrence of an issue by providing the issue ID and occurrence ID.

Instructions

    Get scanner output for a specific occurrence of an issue.

    Args:
        issue_id: The ID of the issue
        occurrence_id: The ID of the occurrence
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issue_idYes
occurrence_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The tool handler function 'get_scanner_output' registered as an MCP tool. It takes issue_id and occurrence_id parameters, fetches scanner output via api.get_scanner_output_all(), and formats the output including plugin name, CVEs, and scanner output lines.
    @mcp.tool()
    async def get_scanner_output(issue_id: int, occurrence_id: int) -> str:
        """
        Get scanner output for a specific occurrence of an issue.
    
        Args:
            issue_id: The ID of the issue
            occurrence_id: The ID of the occurrence
        """
        outputs = api.get_scanner_output_all(issue_id=issue_id, occurrence_id=occurrence_id)
        formatted = []
        for output in outputs:
            plugin_info = f"Plugin: {output.plugin.name}"
            if output.plugin.cve:
                plugin_info += f" (CVEs: {', '.join(output.plugin.cve)})"
            formatted.append(plugin_info)
            formatted.append("Output:")
            formatted.extend(str(line) for line in output.scanner_output)
            formatted.append("")
        return "\n".join(formatted)
  • The tool is registered via the @mcp.tool() decorator on line 129, binding the 'get_scanner_output' async function to the MCP server.
    @mcp.tool()
    async def get_scanner_output(issue_id: int, occurrence_id: int) -> str:
  • The API client method 'get_scanner_output' that performs the HTTP GET request to the Intruder API endpoint /issues/{issue_id}/occurrences/{occurrence_id}/scanner_output/ with pagination params.
    def get_scanner_output(self, issue_id: int, occurrence_id: int,
                          limit: Optional[int] = None, offset: Optional[int] = None) -> PaginatedScannerOutputListList:
        params = {}
        if limit:
            params["limit"] = limit
        if offset:
            params["offset"] = offset
        return PaginatedScannerOutputListList(**self.client.get(f"{self.base_url}/issues/{issue_id}/occurrences/{occurrence_id}/scanner_output/", params=params).json())
  • The API client method 'get_scanner_output_all' which paginates through all scanner output results by calling get_scanner_output in a loop with offset.
    def get_scanner_output_all(self, issue_id: int, occurrence_id: int) -> Generator[ScannerOutputList, None, None]:
        offset = 0
        while True:
            response = self.get_scanner_output(issue_id, occurrence_id, limit=100, offset=offset)
            for output in response.results:
                yield output
            if not response.next:
                break
            offset += len(response.results)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states it 'gets' data, but omits any details about side effects, authorization needs, rate limits, or what the output contains, leaving the agent uninformed.

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 concise with a clear one-line summary followed by parameter details. It could front-load more usage context, but it avoids unnecessary verbosity.

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 presence of an output schema (as per context signals), the description need not detail return values. However, it lacks any mention of error conditions, permissions, or usage notes, which for a simple retrieval tool is serviceable but not fully complete.

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%, so the description must compensate. The description lists parameters with brief explanations ('The ID of the issue/occurrence'), adding basic meaning beyond the schema's integer type. However, no constraints or formats are given, which is adequate but not outstanding.

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 'Get scanner output for a specific occurrence of an issue,' using a specific verb ('Get') and resource ('scanner output'), and distinguishes from sibling tools like get_scan and list_occurrences.

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 explicit guidance on when or when not to use this tool. The description implies usage context but fails to mention prerequisites, alternatives (e.g., using list_occurrences for a broader view), or any conditions.

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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