AgentRPC + gptme: Complete MCP Integration

AgentRPC is a MCP server that Connect to any function, any language, across network boundaries using AgentRPC..

When integrated with gptme, you can:

• Register functions across languages and networks
• Call functions across network boundaries
• List all registered functions across languages

This guide provides step-by-step instructions to set up AgentRPC in gptme, including configuration, examples, and troubleshooting.

What You'll Achieve

After completing this setup:

• AgentRPC will be fully integrated and operational
• You can use AgentRPC tools directly in gptme
• All AgentRPC capabilities will be available for your workflows
• Access to 4 different tools

Prerequisites

Before starting, ensure you have:

• API secret from AgentRPC dashboard
• gptme installed and configured
• Compatible operating system (Terminal, Python, Cross-platform)

Installation

Step 1: Install AgentRPC

Configuration

Step 2: Configure gptme

1. Open gptme settings
2. Navigate to MCP server configuration
3. Add AgentRPC server with appropriate settings
4. Save and restart if needed

Examples

Once configured, you can use AgentRPC in gptme:

Multi-Language Microservices

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Ask gptme: "Call Python ML model from TypeScript app via Go API"

Expected Result: undefined

Cross-Cloud Function Calls

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Ask gptme: "Execute distributed data processing across three clouds"

Expected Result: undefined

Kubernetes Function Registry

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Ask gptme: "List available functions in production cluster"

Expected Result: undefined

Testing Your Setup

1. Launch gptme
2. Verify AgentRPC is available in the tools list
3. Test basic AgentRPC functionality

Troubleshooting

Common Issues

Installation Failed

Symptoms: pip install errors, Missing dependencies

Cause: Python environment or package conflicts

Solution:

• Use virtual environment for clean installation
• Update pip to latest version
• Install with pipx for isolation
• Check Python version compatibility

API Key Issues

Symptoms: Authentication errors, Model access denied

Cause: Missing or invalid API keys

Solution:

• Verify API keys are set correctly
• Check API key permissions and quotas
• Test API keys with curl or other tools
• Review model provider documentation

MCP Server Not Loading

Symptoms: Server load errors, Tools not available

Cause: Server configuration or installation issues

Solution:

• Verify server installation and PATH
• Check MCP server configuration syntax
• Test server independently before gptme integration
• Review gptme logs for connection errors

Terminal Display Issues

Symptoms: Formatting problems, Character encoding errors

Cause: Terminal compatibility or encoding issues

Solution:

• Ensure terminal supports UTF-8 encoding
• Try different terminal applications
• Check terminal color and formatting settings
• Update terminal application to latest version

AgentRPC not appearing in gptme

Symptoms: Server not listed, Tools not available

Cause: Configuration or installation issue

Solution:

• Verify configuration syntax
• Check AgentRPC installation
• Restart gptme
• Check logs for error messages

Next Steps

Now that AgentRPC is integrated with gptme:

• Explore all AgentRPC capabilities through gptme
• Check out other MCP servers that work with gptme
• Join the MCP community for tips and support
• Consider contributing to AgentRPC development

Need Help?

• Search for AgentRPC documentation
• Check the gptme MCP guide
• Join the MCP community discussions