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Mr-Lucasz

Conversational API Test MCP

by Mr-Lucasz

import_curl

Converts a pasted curl command into a YAML API request definition under .mcp/api/, moving credentials to .env.mcp.local and replacing them with {{VARIABLE}}.

Instructions

Turn a curl command the user pasted into a request in a YAML definition under .mcp/api/ (creates the file, or appends to it). Method, URL, query string, headers and JSON / form body are carried over. Credentials (Authorization, cookies, -u, credential-looking fields) are moved to .env.mcp.local and replaced by {{VARIABLE}}, so the YAML stays safe to commit. Fails if requestId already exists.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
curlYesThe curl command, exactly as the user pasted it.
requestIdYesId for the new request, e.g. get_user. Letters, digits and underscores.
descriptionNo
workspaceRootNoAbsolute project path (optional when MCP_WORKSPACE_ROOT is set).
definitionRelativePathNoYAML to create or append to, under .mcp/api/..mcp/api/imported.yaml

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full disclosure burden and does so well: file creation vs. append behavior, credential relocation to `.env.mcp.local` with `{{VARIABLE}}` substitution, which parts of the curl are carried over, and the duplicate-requestId failure mode. These are exactly the side effects and side-channel consequences an agent needs before invoking.

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?

Three sentences, each dense with distinct information, front-loaded with the core transformation and followed by transfer scope, credential handling, and the failure mode. No filler or repetition of the tool name.

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

Completeness4/5

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

For a 5-parameter, mutation-style tool with no annotations and no output schema, the description covers behavior, side effects, and the main failure mode well. It does not describe the return value or the semantics of the optional `description` field, which is a minor remaining gap.

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?

Schema coverage is 80% and the schema already documents `curl`, `requestId`, and `definitionRelativePath`. The description adds meaning beyond that by clarifying the uniqueness constraint on `requestId` (fails on collision) and the parsing scope of the `curl` payload; only the bare `description` parameter gets no added context.

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?

States a specific verb (turn/convert) and resource (curl command into a YAML request definition), and names the destination path `.mcp/api/`. An agent can distinguish this from siblings like `convert_legacy_to_canonical` or `upsert_canonical_api_definition` readily.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear triggering context (a curl command the user pasted) and a failure condition (requestId already exists), which effectively tells the agent when not to call it. It never names alternative tools for adjacent tasks such as validating a request via `dry_run_request` or editing an existing definition via `upsert_canonical_api_definition`.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.