mcp api readiness auditor

    1

    Evaluate API safety and design secure tool contracts for Model Context Protocol (MCP) agent integrations.

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    Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIGitHub CopilotGitHub CopilotGemini CLIGemini CLI+20 more

    mcp api readiness auditor

    Example session with this skill installed

    Audit my /v1/payments API for MCP readiness. It handles transfers and user lookups. We use OAuth2 tokens but don't have idempotency keys on the transfer endpoint yet.

    • Read your context and instructions
    • Compiled the mcp api readiness
    • Generated the document

    I have audited the /v1/payments API against the MCP Safety Framework. The current implementation is

    AMBER (High Risk) due to the lack of idempotency on state-changing operations and broad response schemas.

    MCP Readiness Audit Report

    Tool Map & Risk Classification

    EndpointMCP Tool NameClassificationRisk LevelGap
    POST /transferssend_paymentDestructiveCRITICALMissing idempotency; high financial risk.
    GET /users/{id}get_user_detailsRead-onlyLOWPotential PII leakage if schema isn't filtered.
    GET /balancecheck_balanceRead-onlyNONEReady for exposure.

    Critical Gaps

    GapAffected ToolSeverityMitigation
    No Idempotencysend_paymentHighImplement X-Idempotency-Key requirement in the tool contract.
    PII Exposureget_user_detailsMediumNarrow schema to exclude ssn and internal_flags.
    Missing Approvalsend_paymentHighRequire human_approval: true in the MCP client configuration.

    Redesigned Tool Contract: send_payment

    {
      "name": "send_payment",
      "description": "Transfer funds between accounts. Requires human confirmation.",
      "inputSchema": {
        "type": "object",
        "properties": {
          "amount": { "type": "number", "minimum": 0.01, "maximum": 5000 },
          "currency": { "type": "string", "enum": ["USD", "EUR"] },
          "recipient_id": { "type": "string", "pattern": "^acc_[a-z0-9]+$" },
          "idempotency_key": { "type": "string", "description": "Unique UUID for this transaction" },
          "dry_run": { "type": "boolean", "default": true }
        },
        "required": ["amount", "currency", "recipient_id", "idempotency_key"]
      }
    }
    

    Validation Checklist

    • Agent Usability: PASS. Tools have distinct, verb-based naming.
    • Least Privilege: WARN. get_user_details returns too much metadata.
    • Containment: FAIL. A looping agent could trigger multiple transfers without idempotency.

    Next steps

    1. Implement an idempotency layer on the POST /transfers endpoint.
    2. Update the OpenAPI spec to include a Dry-Run header for agent testing.
    3. Configure your MCP host to intercept send_payment for manual user approval.

    mcp-api-readiness-auditor.pdf

    PDF · document

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Identify destructive API actions requiring human-in-the-loop approvals.Redesign API schemas into narrowed, agent-friendly tool contracts.Map OAuth scopes to specific agent permissions for least-privilege access.Assess idempotency gaps to prevent duplicate actions from agent loops.

    About this skill

    The problem

    Exposing internal APIs directly to AI agents via MCP is dangerous. Standard REST endpoints often lack the idempotency, strict validation, and human-in-the-loop controls required to prevent agents from performing destructive actions or leaking sensitive data.

    What it does

    • Maps existing REST/gRPC/GraphQL endpoints to intended MCP tool names and schemas.
    • Classifies every tool by risk level, identifying destructive actions and potential data leakage.
    • Performs a deep gap analysis on authentication delegation, idempotency, and rate limiting.
    • Generates redesigned tool contracts with narrowed schemas and explicit safety boundaries.
    • Produces a traffic-light readiness report with a phased rollout and kill-switch strategy.

    Frameworks & tools

    Model Context Protocol (MCP), OpenAPI, RAML, GraphQL, OAuth, and RESTful API standards.

    Why this beats prompting it yourself

    A standard prompt lacks a systematic risk classification framework. This skill uses a multi-phase audit workflow that forces checks for IDOR risks, state-change idempotency, and agent-specific failure modes that general LLMs often overlook during ad-hoc reviews.

    Use cases

    • Auditing a legacy CRUD API before building an MCP server for Claude or Cursor.
    • Defining safety boundaries for agents that have write-access to production data.
    • Designing human-in-the-loop workflows for high-value financial or admin actions.
    • Hardening API schemas to reduce LLM hallucinations and token waste.

    Known limitations

    Requires a provided API specification or endpoint list to function. Does not perform live penetration testing or automated traffic analysis.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

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    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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    Recently published to Agensi

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    Trust & safety

    Security scanned

    Verified clean 17 days ago

    • Passed all security checks, Safe to install

    Listed17 days ago

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