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Brucedh

AWS‑IReveal‑MCP

networkinsights_get_findings

Retrieve security findings for AWS network analysis to identify potential vulnerabilities and access scope issues.

Instructions

Retrieve all findings for a given analysis.

Parameters:
    aws_region (str): The AWS region - use 'us-east-1' if not specified.
    analysis_id (str): The ID of the analysis to retrieve findings for.
    max_results (int): Maximum number of findings to return.

Returns:
    JSON list of NetworkInsightsAccessScopeAnalysisFinding objects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aws_regionYes
analysis_idYes
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function decorated with @mcp.tool(), which registers and implements the tool logic to retrieve findings for a Network Insights Access Scope Analysis by paginating through EC2 API calls and returning JSON.
    @mcp.tool()
    async def networkinsights_get_findings(
        aws_region: str,
        analysis_id: str,
        max_results: int = 1
    ) -> str:
        """
        Retrieve all findings for a given analysis.
    
        Parameters:
            aws_region (str): The AWS region - use 'us-east-1' if not specified.
            analysis_id (str): The ID of the analysis to retrieve findings for.
            max_results (int): Maximum number of findings to return.
    
        Returns:
            JSON list of NetworkInsightsAccessScopeAnalysisFinding objects.
        """
        client = boto3.client('ec2', region_name=aws_region)
        findings = []
        next_token = None
        while True:
            kwargs = {
                'NetworkInsightsAccessScopeAnalysisId': analysis_id,
                'MaxResults': max_results
            }
            if next_token:
                kwargs['NextToken'] = next_token
            resp = client.get_network_insights_access_scope_analysis_findings(**kwargs)
            findings.extend(resp.get('AnalysisFindings', []))
            next_token = resp.get('NextToken')
            if not next_token:
                break
        return json.dumps(findings, indent=2, cls=DateTimeEncoder)
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool retrieves findings but doesn't mention authentication requirements, rate limits, pagination behavior (despite 'max_results' parameter), error conditions, or whether this is a read-only operation. The description is minimal and lacks critical behavioral context.

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 efficiently structured with clear sections for purpose, parameters, and returns. Each sentence earns its place by providing essential information without redundancy. The parameter explanations are brief but informative, and the return value is clearly stated.

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 has 3 parameters with no schema descriptions and no annotations, the description does a decent job explaining parameters and the return format. However, it lacks context about the tool's behavior (e.g., pagination, errors), usage relative to siblings, and AWS-specific considerations. The presence of an output schema helps, but more operational context is needed for a complex AWS 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?

The description adds significant value beyond the input schema, which has 0% description coverage. It explains all three parameters: 'aws_region' (with a default value hint), 'analysis_id' (what it represents), and 'max_results' (its purpose). This compensates well for the schema's lack of descriptions, though it could provide more detail about parameter formats 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 'retrieve' and resource 'findings for a given analysis', making the purpose specific. However, it doesn't distinguish this tool from similar sibling tools like 'guardduty_get_findings' or 'accessanalyzer_get_finding', which also retrieve findings but for different AWS services.

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. It doesn't mention prerequisites (e.g., needing an existing analysis), exclusions, or how it differs from sibling tools like 'networkinsights_list_analyses' or 'guardduty_get_findings', leaving the agent with no contextual usage information.

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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