mcp-test-mcp

An MCP server that helps AI assistants test other MCP servers. It provides tools to connect to target MCP servers, discover their capabilities, execute tools, read resources, and test prompts—all through proper MCP protocol communication.

Features

• Connection Management: Connect to any MCP server (STDIO or HTTP transport), auto-detect protocols, track connection state

• Tool Testing: List all tools with complete input schemas, call tools with arbitrary arguments, get detailed execution results

• Resource Testing: List all resources with metadata, read text and binary content

• Prompt Testing: List all prompts with argument schemas, get rendered prompts with custom arguments

• LLM Integration: Execute prompts end-to-end with actual LLM inference, supports template variables and JSON extraction

Installation

Prerequisites: Node.js 16+ and Python 3.11+

Choose your AI coding tool:

Config file location:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

• Windows: %APPDATA%/Claude/claude_desktop_config.json

Configuration:

Or use Claude Code CLI:

Config file location:

• Global: ~/.cursor/mcp.json

• Project: .cursor/mcp.json

Or access via: File → Preferences → Cursor Settings → MCP

Configuration:

Config file location: ~/.codeium/windsurf/mcp_config.json

Or access via: Windsurf Settings → Cascade → Plugins

Configuration:

Requires VS Code 1.99+ with chat.agent.enabled setting enabled.

Config file location:

• Workspace: .vscode/mcp.json

• Global: Run MCP: Open User Configuration from Command Palette

Configuration:

Note: VS Code uses servers instead of mcpServers and recommends camelCase naming.

Config file location: ~/.codex/config.toml

Add via CLI:

Or add manually to config.toml:

To use the execute_prompt_with_llm tool, add environment variables to your configuration:

JSON format (Claude, Cursor, Windsurf, VS Code):

TOML format (Codex):

Quick Start

Once configured, test MCP servers through natural conversation:

• Connect: "Connect to my MCP server at /path/to/server"

• Discover: "What tools does it have?"

• Test: "Call the echo tool with message 'Hello'"

• Status: "What's the connection status?"

• Disconnect: "Disconnect from the server"

Available Tools

Connection Management

• connect_to_server: Connect to a target MCP server (stdio or HTTP)

• disconnect: Close active connection

• get_connection_status: Check connection state and statistics

Tool Testing

• list_tools: Get all tools with complete schemas

• call_tool: Execute a tool with arguments

Resource Testing

• list_resources: Get all resources with metadata

• read_resource: Read resource content by URI

Prompt Testing

• list_prompts: Get all prompts with argument schemas

• get_prompt: Get rendered prompt with arguments

• execute_prompt_with_llm: Execute prompts with actual LLM inference

Utility

• health_check: Verify server is running

• ping: Test connectivity (returns "pong")

• echo: Echo a message back

• add: Add two numbers

Environment Variables

Core

• MCP_TEST_LOG_LEVEL: Logging level (DEBUG, INFO, WARNING, ERROR). Default: INFO

• MCP_TEST_CONNECT_TIMEOUT: Connection timeout in seconds. Default: 30.0

LLM Integration (for execute_prompt_with_llm)

• LLM_URL: LLM API endpoint URL

• LLM_MODEL_NAME: Model name

• LLM_API_KEY: API key

Development

Documentation

• Testing Guide - Complete guide with LLM integration examples

License

MIT License - see LICENSE for details.

Resources

• FastMCP Documentation

• Model Context Protocol Specification

• Cursor MCP Documentation

• Windsurf MCP Documentation

• VS Code MCP Documentation

• Codex MCP Documentation