API Request MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| NO_PROXY | No | 不使用代理的主机列表，用逗号分隔 | |
| HTTP_PROXY | No | HTTP请求的代理服务器地址 | |
| HTTPS_PROXY | No | HTTPS请求的代理服务器地址 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| send_api_requestC | 发送API请求并返回JSON响应，支持多种协议和代理 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap with other tools, making disambiguation perfect. The tool has a clear and distinct purpose of sending API requests, so an agent cannot misselect between non-existent alternatives.
The single tool name 'send_api_request' follows a consistent verb_noun pattern, and with no other tools to compare, there is no inconsistency. The naming is clear and predictable for the server's scope.
A single tool is too few for a server named 'API Request MCP Server', which implies a broader scope for handling API interactions. This minimal set feels thin and incomplete for the apparent purpose, as it lacks operations like request configuration, error handling, or batch processing.
The tool surface is severely incomplete for an API request server. While 'send_api_request' covers the core action, there are obvious gaps such as no tools for managing request headers, authentication, retries, or parsing responses beyond JSON. This will likely cause agent failures in complex API workflows.