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SD Elements MCP Server

api_request

Execute custom API requests to SD Elements endpoints using specified HTTP methods, endpoints, parameters, and body data for integration with the security development lifecycle platform.

Instructions

Make a custom API request to any SD Elements endpoint

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoRequest body data as key-value pairs
endpointYesAPI endpoint (e.g., 'projects/', 'applications/123/')
methodYesHTTP method for the request
paramsNoURL parameters as key-value pairs

Implementation Reference

  • The main handler function for the 'api_request' tool. It is decorated with @mcp.tool() which registers it automatically. The function makes a generic API request using the global api_client and returns JSON-formatted result.
    @mcp.tool()
    async def api_request(ctx: Context, method: str, endpoint: str, params: Optional[Dict[str, Any]] = None, data: Optional[Dict[str, Any]] = None) -> str:
        """Make a generic API request to a custom endpoint. Use when user says 'make a GET/POST/PUT/DELETE request', 'call API endpoint', or 'custom API call'. Do NOT use for specific operations - use dedicated tools like get_project instead."""
        global api_client
        if api_client is None:
            api_client = init_api_client()
        result = api_client.api_request(method, endpoint, params, data)
        return json.dumps(result, indent=2)
  • Import of the tools module which triggers registration of all tools including api_request via their @mcp.tool() decorators.
    from . import tools  # noqa: F401
  • Import of generic.py which registers the api_request tool via @mcp.tool() decorator.
    from .generic import *
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 states the tool makes API requests but fails to mention critical details like authentication requirements, rate limits, error handling, or response formats. For a generic API tool with potential write operations (e.g., POST, DELETE), this lack of transparency is a significant gap.

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 a single, efficient sentence: 'Make a custom API request to any SD Elements endpoint.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's scope, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (generic API requests with multiple HTTP methods including mutating ones like POST/DELETE), no annotations, and no output schema, the description is insufficient. It doesn't cover behavioral aspects like safety, response handling, or error cases, leaving the agent under-informed for proper use in a multi-tool environment.

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 input schema fully documents all four parameters (method, endpoint, data, params) with descriptions and enums. The description adds no additional parameter semantics beyond implying 'any SD Elements endpoint,' which is already covered by the schema. 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: 'Make a custom API request to any SD Elements endpoint.' It specifies the verb ('Make'), resource ('API request'), and target ('SD Elements endpoint'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_project' or 'update_application', which are more specific API calls.

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 the many specific sibling tools (e.g., 'get_project', 'update_application'). It lacks context about prerequisites, such as authentication or endpoint knowledge, and doesn't mention alternatives or exclusions, leaving the agent to guess based on the generic nature of the tool.

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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