mcpmesh/cli repository overview

MCP Mesh CLI Tools

Command-line interface and utilities for managing MCP Mesh distributed applications

The MCP Mesh CLI provides a comprehensive toolkit for deploying, monitoring, and debugging MCP agents in distributed environments. Includes both Go binaries and Python runtime for complete mesh operations.

🚀 Quick Start

⁠Check mesh status

docker run --rm mcpmesh/cli:latest meshctl status

⁠List all agents and their capabilities

docker run --rm mcpmesh/cli:latest meshctl list agents

⁠Test MCP tool calls

docker run --rm mcpmesh/cli:latest meshctl call my-agent process_data '{"input": "test"}'

⁠Interactive mesh exploration

docker run -it mcpmesh/cli:latest bash

🛠️ Included Tools

meshctl - Primary CLI tool

• Agent Management: List, inspect, and monitor agents
• Capability Discovery: Search and match agent capabilities
• Health Monitoring: Check agent and registry health status
• MCP Calls: Execute remote tool calls directly
• Debugging: Trace dependencies and troubleshoot issues

registry - Registry server

• Local Development: Run registry locally for testing
• Backup/Restore: Export and import mesh configurations
• Migration: Database schema management

Python Runtime - Agent execution

• Agent Development: Interactive Python environment with MCP Mesh SDK
• Testing: Validate agents before deployment
• Debugging: Step through agent logic and dependency resolution

📋 Common Commands

⁠Mesh operations

meshctl status # Overall mesh health meshctl list agents # All registered agents meshctl list capabilities # Available capabilities meshctl describe agent my-agent # Agent details

⁠MCP tool calls

meshctl call agent-name tool-name '{"arg": "value"}' meshctl test-connection agent-name # Test agent connectivity

⁠Registry operations

registry --config /config/registry.yaml # Start registry server registry migrate --database-url $DB_URL # Run database migrations

⁠Development

python -c "import mcp_mesh; print('MCP Mesh installed')"

🔧 Configuration

Mount configuration files to customize behavior:

⁠Custom registry configuration

docker run -v $(pwd)/config:/config mcpmesh/cli:latest
registry --config /config/registry.yaml

⁠Development with local code

docker run -v $(pwd):/workspace -w /workspace mcpmesh/cli:latest
python my_agent.py

🎯 Use Cases

• Local Development: Test agents without Kubernetes
• CI/CD Pipelines: Automated testing and deployment
• Production Monitoring: Health checks and debugging
• Mesh Administration: Registry management and maintenance
• Interactive Debugging: Troubleshoot distributed agent issues

📋 Supported Architectures

• linux/amd64 - Intel/AMD 64-bit
• linux/arm64 - ARM 64-bit (Apple Silicon, Graviton)

🔗 Links

• Documentation: https://github.com/dhyansraj/mcp-mesh/tree/main/docs⁠
• CLI Reference: https://github.com/dhyansraj/mcp-mesh/tree/main/docs/cli⁠
• Examples: https://github.com/dhyansraj/mcp-mesh/tree/main/examples⁠
• Source Code: https://github.com/dhyansraj/mcp-mesh⁠

Part of the MCP Mesh ecosystem - see also https://hub.docker.com/r/mcpmesh/registry⁠ and https://hub.docker.com/r/mcpmesh/python-runtime⁠.

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This emphasizes the CLI's role as the primary tool for managing and debugging MCP Mesh deployments, with practical examples of common operations.