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KS-GEN-AI

Web Request MCP Server

by KS-GEN-AI
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JavaScript
Remote

Web Request MCP Server

Execute HTTP requests via MCP (Model Context Protocol)

This is a TypeScript-based MCP server that provides a flexible tool to execute HTTP requests with custom methods, headers, and body content. It enables AI assistants to interact with web APIs and endpoints seamlessly.

Features

http_request

A versatile tool for making HTTP requests with full control over all parameters.

  • Purpose: Execute HTTP requests with custom configuration

  • Parameters:

    • url (required): The target URL (e.g., "https://api.example.com/endpoint")

    • method (optional): HTTP method - GET, POST, PUT, DELETE, PATCH, HEAD, OPTIONS (defaults to GET)

    • headers (optional): Custom headers as key-value pairs

    • body (optional): Request body (string or object, automatically JSON stringified for objects)

    • params (optional): URL query parameters as key-value pairs

  • Behavior:

    • Automatic Content-Type detection for JSON bodies

    • Response truncation for large responses (max 50,000 characters)

    • Comprehensive error handling with status codes

    • Returns full response including status, headers, and data

Example requests:

// Simple GET request
{ url: "https://api.github.com/users/octocat" }

// POST with JSON body
{
  url: "https://api.example.com/data",
  method: "POST",
  headers: { "Authorization": "Bearer token123" },
  body: { name: "John", email: "john@example.com" }
}

// GET with query parameters
{
  url: "https://api.example.com/search",
  params: { q: "search term", limit: "10" }
}

Related MCP server: MCP Server for Crawl4AI

Development

Install dependencies:

npm install

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

Installation

Using with Claude Desktop

To use with Claude Desktop, add the server config:

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "webrequest": {
      "command": "node",
      "args": ["/ABSOLUTE/PATH/TO/webrequest-mcp-server/build/index.js"]
    }
  }
}

Using with Cursor

Add to your Cursor MCP settings configuration file:

{
  "mcpServers": {
    "webrequest": {
      "command": "node",
      "args": ["/ABSOLUTE/PATH/TO/webrequest-mcp-server/build/index.js"]
    }
  }
}

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector:

npm run inspector

The Inspector will provide a URL to access debugging tools in your browser.

Configuration

The server configuration:

  • Max response size: 50,000 characters (responses larger than this are truncated)

  • Supported methods: GET, POST, PUT, DELETE, PATCH, HEAD, OPTIONS

  • Content types: Automatic JSON handling, supports any content type via headers

Use Cases

This MCP server is useful for:

  • Testing and interacting with REST APIs

  • Fetching data from web services

  • Automating HTTP requests in AI workflows

  • Prototyping API integrations

  • Debugging web endpoints

License

MIT License - see LICENSE file for details

Available Tools

1 tool
http_requestA

Execute an HTTP request with custom method, URL, headers, and body. Supports GET, POST, PUT, DELETE, PATCH, and other HTTP methods. The AI can choose all parameters based on the task requirements.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL to send the request to (e.g., "https://api.example.com/endpoint")
bodyNoOptional request body. Can be a string or an object (will be JSON stringified for objects)
methodNoHTTP method to use (GET, POST, PUT, DELETE, PATCH, HEAD, OPTIONS, etc.). Defaults to GET if not specified.
paramsNoOptional URL query parameters as key-value pairs (e.g., {"id": "123", "filter": "active"})
headersNoOptional HTTP headers as key-value pairs (e.g., {"Content-Type": "application/json", "Authorization": "Bearer token"})

TDQS

A3.8/5.0
Behavior2/5

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

No annotations provided, and description fails to disclose potential side effects, security implications, rate limits, or that the tool makes actual external network calls.

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?

Two concise sentences with front-loaded purpose. No redundant information.

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?

Sufficient for basic understanding given schema covers all parameters. However, lacks mention of return value/response and behavioral caveats, slightly limiting completeness for a tool that performs external requests.

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 baseline is 3. The description adds no additional meaning beyond the schema, merely stating that AI can choose parameters.

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?

Clearly states 'Execute an HTTP request' and lists customizable components (method, URL, headers, body). The verb and resource are specific and unambiguous.

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?

Implicitly suggests use for any HTTP request (AI chooses parameters). No explicit when-not-to-use, but with no sibling tools, differentiation is unnecessary.

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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TDQS

A4/5.0
Disambiguation5/5

Only one tool exists, so there is no ambiguity. The tool's purpose is clearly defined for HTTP requests.

Naming Consistency5/5

With a single tool, naming consistency is not applicable but trivially consistent. The name 'http_request' is clear and follows a common pattern.

Tool Count4/5

The server has only one tool, which is minimal but arguably sufficient given the broad scope of HTTP requests it supports. It is slightly under but reasonable.

Completeness4/5

The tool covers all standard HTTP methods and allows custom headers and body, making it fairly complete for basic web requests. However, it may lack support for advanced features like cookie handling or redirect following.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

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