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Mr-Lucasz

Conversational API Test MCP

by Mr-Lucasz

execute_api_flow

Runs a sequence of API requests in one MCP call, supporting retries, polling, assertions, optional steps, and stop-on-error to chain tests without manual curl.

Instructions

Run a sequence of requestIds in a single MCP round trip. Pass inline steps, or flowName to run a flow declared under flows: in the definition. Each step supports retry, poll (via jsonPath), an inline assert (same shape as assert_response), optional, and jsonPathSelect to get that step's body back ($ for all of it) without a follow-up call. stopOnError halts at the first failing required step.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stepsNoInline steps. Provide either `steps` or `flowName`.
flowNameNoName of a flow declared under `flows:` in the definition.
stopOnErrorNo
workspaceRootNoOptional when MCP_WORKSPACE_ROOT is set.
responseDetailNominimal: requestId/ok/status per step. summary: + durationMs and captured values. per_step: + each step's body (capped). A step's own `jsonPathSelect` returns its body at any level.summary
definitionRelativePathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does reasonably well: it discloses step-level behaviors (retry, poll via jsonPath, inline assert, optional, jsonPathSelect) and that `stopOnError` halts at the first failing required step. It omits auth/permission needs and write-vs-read safety, but the operational behavior is substantially covered.

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?

Four sentences, front-loaded with the purpose and packed with high-value detail using no filler. The parameter capabilities are enumerated compactly, and nothing is redundant with the schema's own descriptions.

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 complex nested-steps tool with no output schema, the description is fairly complete: it covers steps, flowName, stopOnError, and the per-step features. It leaves responseDetail, definitionRelativePath, workspaceRoot, and acceptStatus to the schema, which is acceptable but leaves minor gaps given the tool's complexity.

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?

At 67% schema coverage the description meaningfully compensates: it defines the `steps` vs `flowName` alternative, explains `jsonPathSelect` ("$ for all of it") and its follow-up-call avoidance, and cross-references `assert` as "same shape as assert_response." This adds semantics beyond the schema for several of the six parameters.

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?

States a specific verb and resource with scope: "Run a sequence of requestIds in a single MCP round trip." This clearly differentiates the batch/flow concept from a single-request tool, though it never names the sibling (execute_api_request) it contrasts with, so the differentiation is implicit rather than explicit.

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

Usage Guidelines3/5

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

The description explains HOW to invoke (inline `steps` vs `flowName`) but not WHEN to choose this tool over execute_api_request, dry_run_request, or run_vander_checks. Usage context is only implied by the single-round-trip framing, with no exclusions or explicit alternative routing.

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