AgentRPC

AgentRPC avatar

by nadeesha

Official Integrations

A universal RPC layer for AI agents. Connect to any function, any language, any framework, in minutes.

What is AgentRPC

AgentRPC

NPM Version GitHub go.mod Go version PyPI - Python Version License

Universal RPC layer for AI agents across network boundaries and languages

Overview

AgentRPC allows you to connect to any function, in any language, across network boundaries. It's ideal when you have services deployed in:

  • Private VPCs
  • Kubernetes clusters
  • Multiple cloud environments

AgentRPC wraps your functions in a universal RPC interface, connecting them to a hosted RPC server accessible through open standards:

  • Model Context Protocol (MCP)
  • OpenAI-compatible tool definitions (OpenAI, Anthropic, LiteLLM, OpenRouter, etc.)

How It Works

  1. Registration: Use our SDK to register functions and APIs in any language
  2. Management: The AgentRPC platform (api.agentrpc.com) registers the function and monitors its health
  3. Access: Receive OpenAPI SDK compatible tool definitions and a hosted MCP server for connecting to compatible agents

Key Features

Feature Description
Multi-language Support Connect to tools in TypeScript, Go, Python and .NET (coming soon)
Private Network Support Register functions in private VPCs with no open ports required
Long-running Functions Long polling SDKs allow function calls beyond HTTP timeout limits
Full Observability Comprehensive tracing, metrics, and events for complete visibility
Automatic Failover Intelligent health tracking with automatic failover and retries
Framework Compatibility Out-of-the-box support for MCP and OpenAI SDK compatible agents

Getting Started

Quick Start

Follow the quick start example on our docs site.

Examples

Explore working examples in the examples directory.

MCP Server

The AgentRPC TypeScript SDK includes an optional MCP (Model Context Protocol) server.

ANGENTRPC_API_SECRET=YOUR_API_SECRET npx agentrpc mcp

This launches an MCP-compliant server for external AI models to interact with your registered tools.

Claude Desktop Integration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "agentrpc": {
      "command": "npx",
      "args": [
        "-y",
        "agentrpc",
        "mcp"
      ],
      "env": {
        "AGENTRPC_API_SECRET": "<YOUR_API_SECRET>"
      }
    }
  }
}

More Info

Cursor Integration

Add to your ~/.cursor/mcp.json:

{
  "mcpServers": {
    "agentrpc": {
      "command": "npx",
      "args": ["-y", "agentrpc", "mcp"],
      "env": {
        "AGENTRPC_API_SECRET": "<YOUR_API_SECRET>"
      }
    }
  }
}

More Info

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

This repository contains all the open-source components and SDKs for AgentRPC.

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Frequently Asked Questions

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.