Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@HTTP MCP Server GET https://jsonplaceholder.typicode.com/posts/1"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A Model Context Protocol (MCP) server that enables AI agents to send HTTP requests to any endpoint with full control over methods, headers, query parameters, and request bodies.
Note: This MCP server only supports stdio transport.
Support for major HTTP methods (GET, POST, PUT, PATCH, DELETE, QUERY)
Custom headers configuration
Query parameter handling with proper URL encoding
Request body support for POST/PUT/PATCH/QUERY
Comprehensive error handling
TypeScript with strict type safety
Clean, modular architecture
STDIO transport support for seamless integration with MCP clients
Install the package globally using npm:
npm install -g @jules-tnk/ts-http-mcpOr use npx to run it directly:
npx @jules-tnk/ts-http-mcpAdd the following configuration to your Claude Desktop config file (claude_desktop_config.json):
Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Linux: ~/.config/claude/claude_desktop_config.json
{
"mcpServers": {
"http-mcp": {
"command": "npx",
"args": ["@jules-tnk/ts-http-mcp"]
}
}
}After updating the configuration, restart Claude Desktop to load the MCP server.
Related MCP server: cURL MCP Server
For other MCP clients that support stdio transport, configure them to run:
npx @jules-tnk/ts-http-mcppnpm installpnpm buildpnpm startTo test the MCP server locally, you can run it directly and interact with it through stdio:
pnpm startThe server will start and listen for MCP protocol messages on stdin/stdout.
Once configured with your MCP client, the HTTP MCP server provides the following capabilities:
GET requests: Retrieve data from any HTTP endpoint
QUERY requests: Send safe, idempotent requests with request bodies
POST requests: Send data to endpoints that accept POST requests
PUT/PATCH requests: Update resources on remote servers
DELETE requests: Remove resources from remote servers
Custom headers: Add authentication, content-type, and other headers
Query parameters: Include URL parameters with proper encoding
Request bodies: Send JSON, form data, or raw content for supported body-capable methods
The server handles all the HTTP communication details, error handling, and response processing, making it easy for AI agents to interact with web APIs and services.
MIT License - see the LICENSE.md file for details.
Send an HTTP request to any endpoint with custom headers, query parameters, and body
Inputs: url (required), method (required), body, headers, +1 more.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 1 tool
With only one tool, there is no possibility of confusion between tools. The tool's purpose is clear and unambiguous.
The single tool follows a clear verb_noun convention, and the name accurately describes its function. Consistency is trivially maintained.
One tool is appropriate for a server dedicated solely to HTTP requests. While the count is below the typical range, it is not excessive or deficient for the narrow scope.
The tool supports full HTTP request customization, covering all methods and parameters. There are no obvious missing operations within the domain of making HTTP requests.
Reliable web access for AI agents: smart HTTP, rotating proxies, and full-browser rendering.
Pay-per-use agent tools: schedule HTTP calls, extract pages, PDFs, OG images, QR codes, short links.
Let agents make HTTP requests later: schedule, retry, cron, watch jobs, receive webhooks.
13 privacy-first network, auth & web tools for AI agents — no API key, 60 req/min free.
