MCP CLI

A command-line interface skill for interacting with Model Context Protocol servers, enabling developers to test, debug, and manage MCP tools and resources directly from the terminal.

What Is This?

Overview

This skill provides guidance for using the MCP CLI to connect to MCP servers, invoke tools, query resources, and inspect protocol messages. It covers server connection management, tool discovery, parameter passing, and response formatting for efficient MCP development workflows.

Who Should Use This

Perfect for developers building MCP servers who need testing tools, DevOps engineers managing MCP deployments, and AI integration teams debugging tool communication between clients and servers.

Why Use It?

Problems It Solves

Testing MCP servers typically requires a full AI client setup, making iteration slow. Without a dedicated CLI, developers cannot easily invoke individual tools, inspect responses, or debug protocol-level issues. The MCP CLI provides direct server interaction for rapid development and troubleshooting.

Core Highlights

• Direct Tool Invocation - Call MCP tools from terminal with JSON parameters
• Resource Inspection - Query and browse server resources interactively
• Protocol Debugging - View raw JSON-RPC messages for troubleshooting
• Server Management - Connect, disconnect, and switch between servers
• Response Formatting - Pretty-print tool results and resource content

How to Use It?

Basic Usage

Ask Claude about using the MCP CLI, and this skill will guide tool invocation and debugging.

Scenario 1: Connecting and Invoking Tools

Ask Claude: "How do I test my MCP server from the command line?"

Claude will show:

mcp connect -- node server.js

mcp tools list

mcp tools call search_files '{"pattern": "*.ts", "directory": "src"}'

mcp tools call calculate --operation add --a 10 --b 20

mcp --verbose tools call search_files '{"pattern": "*.ts"}'

Scenario 2: Resource Management

Tell Claude: "Browse resources on my MCP server"

Claude will demonstrate:

mcp resources list

mcp resources read "file:///src/main.ts"

mcp resources templates

mcp resources subscribe "db:///users"

Real-World Examples

MCP Server Development

A developer building a database query MCP server used the CLI to test each tool individually. Direct invocation with JSON parameters caught schema validation bugs before integrating with Claude, reducing debugging cycles by 80%.

Production Diagnostics

An operations team used the MCP CLI to diagnose a failing tool in production. Verbose mode revealed a malformed JSON-RPC response that was silently dropped by the AI client, identifying the root cause in minutes.

Advanced Tips

Scripted Testing

Combine MCP CLI commands in shell scripts for automated integration testing. Pipe tool results to jq for JSON validation and field extraction in CI pipelines.

Multiple Server Profiles

Configure named server profiles for different environments (development, staging, production) to quickly switch contexts without re-entering connection details.

When to Use It?

Use Cases

• Server Testing - Invoke individual MCP tools during development
• Protocol Debugging - Inspect raw JSON-RPC messages for errors
• Integration Testing - Script automated tests for MCP server endpoints
• Resource Browsing - Explore available resources and their content
• Deployment Verification - Validate MCP servers after deployment

Related Topics

When you ask Claude these questions, this skill will activate:

• "How do I use the MCP CLI?"
• "Test my MCP server from terminal"
• "Debug MCP tool invocation"
• "List MCP server tools and resources"

Important Notes

Requirements

• MCP CLI installed (npm install -g @modelcontextprotocol/cli)
• Node.js 18+ for running MCP servers
• MCP server running locally or accessible via network
• Basic understanding of JSON-RPC protocol

Usage Recommendations

Do:

• Use verbose mode - Enable protocol logging when debugging issues
• Test tools individually - Verify each tool before full integration
• Validate JSON parameters - Ensure parameter format matches tool schema
• Script repetitive tests - Automate common test sequences

Don't:

• Don't test only happy paths - Include error cases and edge conditions
• Don't skip schema validation - Verify parameter types match expectations
• Don't ignore timeouts - Set appropriate timeout values for slow tools

Limitations

• CLI supports stdio transport primarily, HTTP transport may need additional config
• Interactive prompts not supported in scripted mode
• Large response payloads may be truncated in terminal output
• Real-time resource subscriptions require persistent connection