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mcp-swagger-reader

mcp-swagger-reader

by momei-LJM
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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get_schemas

Retrieve all data models and schemas for a project from its Swagger/OpenAPI specification by providing the project name, enabling direct inspection of available schemas.

Instructions

获取指定项目的所有数据模型/Schemas

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": {
      "projectName": "<projectName>"
    },
    "name": "get_schemas"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectNameYes项目名称

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

B3.3/5.0
Behavior2/5

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

There are no annotations, so the description carries the full behavioral disclosure burden, but it only restates the core function. It does not mention output format, pagination, error behavior, or whether any project validation occurs.

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, compact sentence with no filler. It front-loads the action and resource and does not repeat information that is already in the schema.

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

Completeness3/5

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

For a one-parameter list tool the description is minimally viable, but it lacks usage context and return information, and there is no output schema to compensate. An agent can likely call it correctly, but needs to infer behavior and alternatives.

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?

The only parameter, projectName, is already fully described in the schema with 100% coverage. The description's reference to '指定项目' adds no new semantic detail beyond the schema, so the baseline score of 3 applies.

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 states a specific action ('get') and resource ('all data models/Schemas') scoped to a named project. This clearly differentiates it from siblings like get_api_endpoints and get_api_detail, which target different resource types.

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?

No guidance is provided on when to use this tool instead of the sibling tools, nor are any preconditions or exclusion cases mentioned. The description does not help the agent choose between get_schemas, get_api_detail, or search_apis beyond naming the resource.

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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