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FedRAMP Docs MCP Server

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get_evidence_examples

Find automation-friendly evidence collection sources for FedRAMP KSI compliance, including APIs, CLI commands, and artifacts.

Instructions

Get suggested evidence examples for KSI compliance. Returns automation-friendly evidence collection sources (APIs, CLI commands, artifacts) for each KSI. NOTE: These are community suggestions, not official FedRAMP guidance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
themeNoFilter by KSI theme (e.g., IAM, CNA, AFR)
idNoGet evidence for a specific KSI item ID
includeRetiredNoInclude retired KSIs in results (default: true for backwards compatibility)

Implementation Reference

  • The main handler implementation for the get_evidence_examples tool, including the execute function that loads data, filters KSIs, and constructs the response.
    export const getEvidenceExamplesTool: ToolDefinition<
      typeof schema,
      EvidenceExamplesResult
    > = {
      name: "get_evidence_examples",
      description:
        "Get suggested evidence examples for KSI compliance. Returns automation-friendly evidence collection sources (APIs, CLI commands, artifacts) for each KSI. NOTE: These are community suggestions, not official FedRAMP guidance.",
      schema,
      execute: async (input) => {
        const evidenceData = loadEvidenceExamples();
        const ksiItems = getKsiItems();
    
        const disclaimer = evidenceData?.disclaimer ??
          "These evidence examples are community suggestions to help with FedRAMP compliance automation. They are NOT official FedRAMP guidance. Always verify requirements with official FedRAMP documentation at https://fedramp.gov";
    
        // Filter KSI items based on input
        let filtered: KsiItem[] = ksiItems;
    
        if (input.theme) {
          const themeLower = input.theme.toLowerCase();
          filtered = filtered.filter(
            (item) => item.category?.toLowerCase() === themeLower,
          );
        }
    
        if (input.id) {
          const idUpper = input.id.toUpperCase();
          filtered = filtered.filter((item) => item.id.toUpperCase() === idUpper);
        }
    
        // Build example items with evidence examples
        let items: EvidenceExampleItem[] = filtered.map((ksi) => {
          // Get evidence examples for this KSI from our data file
          const evidenceExample = evidenceData?.examples[ksi.id];
    
          return {
            ksiId: ksi.id,
            ksiName: ksi.title ?? evidenceExample?.name ?? ksi.id,
            ksiStatement: ksi.statement ?? ksi.description,
            theme: ksi.category ?? ksi.theme ?? "",
            impact: ksi.impact,
            evidence: evidenceExample?.evidence ?? [],
            retired: evidenceExample?.retired,
          };
        });
    
        // Filter out retired KSIs if requested
        if (input.includeRetired === false) {
          items = items.filter((item) => !item.retired);
        }
    
        // Get unique themes
        const themes = [...new Set(items.map((item) => item.theme).filter(Boolean))].sort();
    
        return {
          disclaimer,
          total: items.length,
          items,
          themes,
        };
      },
    };
  • Zod schema defining the input parameters for the tool: theme (optional filter), id (optional specific KSI), includeRetired (boolean, default true).
    const schema = z.object({
      theme: z
        .string()
        .optional()
        .describe("Filter by KSI theme (e.g., IAM, CNA, AFR)"),
      id: z.string().optional().describe("Get evidence for a specific KSI item ID"),
      includeRetired: z
        .boolean()
        .optional()
        .default(true)
        .describe("Include retired KSIs in results (default: true for backwards compatibility)"),
    });
  • Import of the getEvidenceExamplesTool.
    import { getEvidenceExamplesTool } from "./get_evidence_examples.js";
  • Registration of all tools including getEvidenceExamplesTool in the registerTools function called by the MCP server.
    export function registerTools(server: McpServer): void {
      registerToolDefs(server, [
        // Document discovery
        listFrmrDocumentsTool,
        getFrmrDocumentTool,
        listVersionsTool,
        // KSI tools
        listKsiTool,
        getKsiTool,
        filterByImpactTool,
        getThemeSummaryTool,
        getEvidenceExamplesTool,
        // Control mapping tools
        listControlsTool,
        getControlRequirementsTool,
        analyzeControlCoverageTool,
        // Search & lookup tools
        searchMarkdownTool,
        readMarkdownTool,
        searchDefinitionsTool,
        getRequirementByIdTool,
        // Analysis tools
        diffFrmrTool,
        grepControlsTool,
        significantChangeTool,
        // System tools
        healthCheckTool,
        updateRepositoryTool,
      ]);
  • Helper function to load the evidence-examples.json data file used by the tool.
    function loadEvidenceExamples(): EvidenceExamplesData | null {
      try {
        // Look for evidence-examples.json in data directory (relative to package root)
        const dataPath = join(__dirname, "..", "..", "data", "evidence-examples.json");
        const content = readFileSync(dataPath, "utf-8");
        return JSON.parse(content) as EvidenceExamplesData;
      } catch {
        // If file doesn't exist or can't be parsed, return null
        return null;
      }
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the output includes 'automation-friendly evidence collection sources' and notes the community-sourced nature, but it lacks details on permissions, rate limits, pagination, or error handling. For a tool with no annotations, this leaves significant gaps in understanding its operational behavior.

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 concise and front-loaded, with two sentences that efficiently convey the tool's purpose and an important caveat. Every sentence adds value without redundancy, making it easy to parse quickly.

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 (3 parameters, no output schema, no annotations), the description is adequate but incomplete. It explains what the tool returns but lacks details on output format, error cases, or integration with sibling tools. Without annotations or output schema, more behavioral context would improve completeness.

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 schema already documents all three parameters thoroughly. The description does not add any parameter-specific semantics beyond what's in the schema, such as examples for 'theme' values or clarification on 'includeRetired'. This meets the baseline for high schema coverage.

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: 'Get suggested evidence examples for KSI compliance' with specific details about what it returns ('automation-friendly evidence collection sources') and distinguishes it from official guidance. However, it doesn't explicitly differentiate from sibling tools like 'get_ksi' or 'list_ksi', which might also retrieve KSI-related information.

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 minimal usage guidance. It mentions that results are 'community suggestions, not official FedRAMP guidance,' which offers some context on reliability, but it doesn't specify when to use this tool versus alternatives like 'get_ksi' or 'list_ksi' for KSI-related queries, nor does it outline prerequisites or exclusions.

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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