MCP HTTP Client Server
A powerful MCP server for making HTTP requests, GraphQL queries, and TCP/Telnet connections from AI assistants.
README
<p align="center"> <img src="mcp-http.png" alt="MCP HTTP Client" title="MCP-HTTP-CLIENT" align="right" width="64"/> </p>
MCP HTTP Client Server
A powerful Model Context Protocol (MCP) server for making HTTP requests, GraphQL queries, and TCP/Telnet connections from AI assistants. Inspired by Postman but designed for AI-native workflows with enhanced response formatting, intelligent caching, and multiple content type support.
Why Use This?
- Seamlessly integrates with AI assistants like Claude
- 13.7x faster with intelligent LRU caching
- Auto-formatted JSON, status emojis, performance metrics
- JSON, form-data, URL-encoded - all supported
- very request shows response time
- atural language commands, no complex setup
Installation
Choose your preferred installation method:
Option 1: npm (Recommended for easy setup)
npm install -g @mcp/http-client
Option 2: Homebrew (macOS/Linux)
brew tap ferPrieto/mcp-http-client
brew install mcp-http-client
Option 3: GitHub Packages (for Kotlin/JVM projects)
Add the repository and dependency to your build.gradle.kts:
repositories {
maven {
url = uri("https://maven.pkg.github.com/ferPrieto/MCP-Http-Client")
credentials {
username = project.findProperty("gpr.user") as String? ?: System.getenv("GITHUB_ACTOR")
password = project.findProperty("gpr.key") as String? ?: System.getenv("GITHUB_TOKEN")
}
}
}
dependencies {
implementation("ferprieto.mcp:httpclient:1.0.0")
}
Note: GitHub Packages requires authentication. Generate a Personal Access Token with read:packages scope.
Option 4: Build from Source
git clone https://github.com/ferPrieto/MCP-Http-Client.git
cd MCP-Http-Client
./gradlew clean build
This generates build/libs/mcp-http-client-all.jar.
Configuration
Add to your MCP client configuration file:
- Cursor:
~/.cursor/mcp.json - Claude Desktop:
~/Library/Application Support/Claude/claude_desktop_config.json
If installed via npm:
{
"mcpServers": {
"http-client": {
"command": "npx",
"args": ["@mcp/http-client"]
}
}
}
If installed via Homebrew:
{
"mcpServers": {
"http-client": {
"command": "mcp-http-client"
}
}
}
If using JAR directly:
{
"mcpServers": {
"http-client": {
"command": "java",
"args": ["-jar", "/path/to/mcp-http-client-all.jar"]
}
}
}
Comparison with Postman
| Feature | MCP HTTP Client | Postman |
|---|---|---|
| Interface | 🤖 Natural Language | 🖱️ GUI |
| Setup Time | ⚡ 1 minute | ⏱️ 5+ minutes |
| HTTP Methods | ✅ All | ✅ All |
| GraphQL | ✅ Native | ✅ Yes |
| TCP/Telnet | ✅ Yes | ❌ No |
| Content Types | ✅ JSON, Form, URL-encoded | ✅ Many |
| Response Formatting | ✅ Auto pretty-print | ✅ Yes |
| Performance Cache | ✅ 13.7x faster | ❌ No |
| Response Time | ✅ Auto-tracked | ✅ Yes |
| Cost | 🆓 Free & Open Source | 💰 Free/Paid |
| AI Integration | ✅ Native | ❌ Manual |
Advanced Features
Content-Type Auto-Detection
The server automatically:
- Detects JSON responses and pretty-prints them
- Sets appropriate
Content-Typeheaders based onbodyType - Handles form-data with proper multipart boundaries
- URL-encodes form parameters automatically
Performance Metrics
Every request automatically tracks:
- Total request duration
- Response size
- Status codes
- Timing information
Roadmap
Future features planned for upcoming releases:
- Collections: Save and organize API requests (like Postman collections)
- Environments: Manage variables across different environments (Dev, Staging, Production)
- Authentication Helpers: Built-in support for Basic Auth, Bearer Token, API Key, OAuth2
- Request Chaining: Use response values in subsequent requests with variable substitution
- Postman Import: Import existing Postman collections for easy migration
License
MIT License
Made with ❤️ for the AI-native development workflow. Simpler than Postman, faster than manual curl commands, perfect for AI assistants!
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.