AgentRPC - Universal Interoperability Layer

A foundational remote invocation system enabling AI agents to bridge environmental and linguistic divides.

Conceptual Framework

AgentRPC empowers developers to invoke any routine, irrespective of its deployment geography or underlying code base. This abstraction is critically valuable for systems operating within: - Isolated Private Networks (VPCs) - Container Orchestration Platforms (Kubernetes) - Heterogeneous Multi-Cloud Architectures

AgentRPC encapsulates target routines within a unified, cross-environment communication facade, exposing them via a central service accessible through industry-accepted specifications:

• Model Context Protocol (MCP)
• Standardized Tool Schemas for LLMs (e.g., OpenAI function calling, Anthropic, LiteLLM, OpenRouter integrations)

Operational Flow

1. Endpoint Declaration: Leverage the provided Software Development Kits (SDKs) to declare available functions and API endpoints across your chosen languages.
2. Orchestration: The centralized AgentRPC management plane (hosted at api.agentrpc.com) ingests these declarations and continuously monitors the operational status of the registered endpoints.
3. Consumption Interface: Consumers receive interoperable tool specifications (OpenAPI format compatible) alongside access to a centrally hosted MCP endpoint for seamless agent connectivity.

Core Capabilities

Capability	Detailed Explanation
Polyglot Interfacing	Seamless connection to services implemented in TypeScript, Go, Python, and forthcoming .NET support.
Air-Gapped Access	Ability to register and call functions residing within secure, private network segments without necessitating public exposure (zero open firewall ports).
Extended Execution Windows	SDK mechanisms supporting long-polling ensure function execution can surpass conventional HTTP request timeouts.
End-to-End Visibility	Integrated tracing apparatus, performance metrics gathering, and event logging for comprehensive system introspection.
Resilience Mechanisms	Automated system health checks enabling intelligent redirection and transparent retry policies upon failure detection.
Ecosystem Alignment	Native compatibility layers supporting agents built upon MCP and OpenAI's tooling paradigms.

Deployment Initiation

Rapid Provisioning Guide

Consult the official documentation's quick start guide for immediate setup instructions.

Illustrative Deployments

Working code samples are available within the examples directory.

MCP Gateway Service

The AgentRPC SDK for TypeScript contains an integrated optional service capable of acting as an MCP endpoint listener.

sh ANGENTRPC_API_SECRET=YOUR_API_SECRET npx agentrpc mcp

Executing this command initiates an MCP-compliant gateway, enabling external artificial intelligence models to invoke your registered functionalities.

Integration with Claude Desktop

Modify your claude_desktop_config.json configuration file as follows:

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

Further Details on Integration

Integration with Cursor IDE

Adjust your ~/.cursor/mcp.json configuration:

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

Cursor MCP Documentation

Governance

This software is distributed under the terms of the Apache License, Version 2.0 (refer to the LICENSE file for specifics).

This repository houses all source code artifacts and Software Development Kits pertaining to the AgentRPC ecosystem.

WIKIPEDIA: Cloud infrastructure is defined by the International Organization for Standardization (ISO) as "a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction."