Skip to main content
Glama
lstpsche

@lstpsche/apidog-mcp

by lstpsche

apidog_export_curl

Turn API endpoints into ready-to-run curl commands with placeholder values. Export from Apidog to simplify testing and integration.

Instructions

Export endpoints as ready-to-use curl command examples with placeholder values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
moduleYesModule name
baseUrlYesBase URL for the API (e.g. https://api.example.com)
projectNoProject name. Required when multiple projects are configured, optional otherwise.
filterTagNoFilter by tag name
filterPathNoFilter by path substring
filterMethodNoFilter by HTTP method
includeHeadersNoExtra headers to include (e.g. {"Authorization": "Bearer <token>"})
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It only mentions the output format and placeholder values, but does not state whether the tool is read-only, whether it makes network requests, or how placeholders are represented. This is a significant gap for a tool that could potentially access live endpoints.

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, concise sentence that conveys the core functionality without wasted words. It is appropriately front-loaded with the action and output.

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?

The description is too sparse for a tool with 7 parameters and no output schema. It fails to mention that the tool supports filtering by tag/path/method, custom headers, or the optional project parameter. These capabilities are only discoverable in the schema, which places extra burden on the agent to infer them.

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 parameters are well-documented. The description adds no additional meaning beyond the schema, so the baseline of 3 is appropriate.

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 exports endpoints as curl command examples with placeholder values. This specific verb+resource+output format distinguishes it from sibling tools like export_postman and export_markdown.

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?

The description provides a clear context: use this tool when you need curl command examples. It does not explicitly mention alternatives, but the format is self-evident, so the intended use case is fairly clear.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/lstpsche/apidog-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server