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Swagger Testcase MCP

Swagger Testcase MCP

by eyaushev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

compare_specs

Compare two OpenAPI specification versions to detect endpoint changes, schema modifications, and breaking changes for API version analysis.

Instructions

Compare two versions of an OpenAPI spec. Detects added/removed/modified endpoints, schema changes, and breaking changes.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "old_source": "<old_source>",
      "new_source": "<new_source>"
    },
    "name": "compare_specs"
  }
}

Input Schema

NameRequiredDescriptionDefault
old_sourceYesOld spec source: URL or file path
new_sourceYesNew spec source: URL or file path
auth_headerNoAuthorization header value, e.g. "Bearer eyJ..." or "Basic dXNlcjpwYXNz"
headersNoAdditional HTTP headers as key-value pairs, e.g. {"X-API-Key": "abc123"}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
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 mentions the tool 'detects' changes but doesn't specify output format, whether it's read-only or has side effects, error handling, or performance considerations. For a tool with 4 parameters and no annotations, this leaves significant behavioral gaps.

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 that front-loads the core purpose and details key functionalities. Every word earns its place, with no redundancy or fluff, 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 (comparing OpenAPI specs with 4 parameters, no output schema, and no annotations), the description is incomplete. It lacks details on output format, error cases, authentication needs implied by 'auth_header', and how breaking changes are reported. This leaves the agent under-informed for effective use.

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 parameters thoroughly. The description adds no parameter-specific information beyond implying the tool compares 'two versions', which aligns with 'old_source' and 'new_source'. It doesn't explain parameter interactions or provide examples beyond what the schema offers.

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?

The description clearly states the tool's purpose with specific verbs ('Compare') and resources ('two versions of an OpenAPI spec'), and distinguishes it from siblings by focusing on comparison rather than analysis, validation, or generation. It explicitly mentions what gets compared: 'added/removed/modified endpoints, schema changes, and breaking changes'.

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 alternatives like 'analyze_endpoint' or 'validate_spec'. It doesn't mention prerequisites, such as needing accessible spec sources, or exclusions, like not being suitable for single-spec validation. Usage context is implied but not explicit.

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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