🧪 MCP Server Testing Application
LocalAbout 🧪 MCP Server Testing Application
A Node.js web app for developers to check connectivity and basic functionality of MCP-compatible backends. It tests health endpoints and sample runs, then presents the server's response and execution details.
Key features
- 01Check server connectivity
- 02Validate /health or HEAD
- 03Send a sample prompt to /run
- 04Display response, result, steps, and schema
Use cases
- 01Verify an MCP backend is reachable
- 02Check that /run returns a usable response
MCP support
It tests connectivity and basic functionality of MCP servers by checking health and sending a sample prompt to `/run`.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project README🧪 MCP Server Testing Application
A simple Node.js web application that tests connectivity and basic functionality of a Modular Computational Prompting (MCP) server. Useful for developers building or integrating with MCP-compatible AI backends.
🚀 Features
- Test basic connectivity to any MCP server.
- Validate
/healthendpoint or fallback toHEADrequest. - Send a sample prompt to the
/runendpoint to verify functionality. - Displays:
- Server response
- Result/answer
- Execution steps/thoughts
- Output schema
📦 Tech Stack
- Node.js + Express
- Axios for HTTP requests
- HTML frontend (in
public/directory)
🛠️ Installation & Setup
- Clone the repository
git clone https://github.com/UdhayaParameshwaran-ai/mcp-server-tester.git cd mcp-server-tester - Install dependencies
npm install - Start the application
node server.js - Visit in your Brower http://localhost:3000/
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.