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agentrpc

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AgentRPC is a universal RPC client that enables AI agents to connect seamlessly to any function across languages and network boundaries. It supports deployment in private VPCs, Kubernetes clusters, and multiple cloud environments, wrapping functions in a standardized RPC interface compatible with MCP and OpenAI-style tool definitions. This client simplifies integration of AI agents with diverse backend services, enhancing interoperability and scalability in complex distributed systems.

Use This MCP client To

Connect AI agents to functions across different programming languages Integrate AI agents with services in private VPCs securely Enable AI agents to call functions deployed in Kubernetes clusters Bridge AI agents with multi-cloud backend services Standardize AI agent interactions using MCP and OpenAI-compatible tool definitions Facilitate cross-network function calls for AI workflows Simplify deployment of AI agent RPC interfaces in complex environments

README

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.)

deployment

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

agentrpc FAQ

How does AgentRPC handle cross-language function calls?
AgentRPC wraps functions in a universal RPC interface, enabling AI agents to call functions regardless of their programming language or framework.
Can AgentRPC be used in private network environments?
Yes, it supports deployment in private VPCs, Kubernetes clusters, and multi-cloud environments, ensuring secure connectivity.
What protocols does AgentRPC support?
It supports the Model Context Protocol (MCP) and OpenAI-compatible tool definitions, including OpenAI, Anthropic, LiteLLM, and OpenRouter.
How quickly can I integrate AgentRPC with my existing services?
AgentRPC is designed for rapid integration, allowing connection to any function in minutes across languages and networks.
Is AgentRPC limited to specific cloud providers?
No, it works across multiple cloud environments and on-premises deployments.
Does AgentRPC support secure communication?
Yes, it is designed to operate securely within private networks and cloud environments, respecting network boundaries.
Can AgentRPC facilitate multi-step AI workflows?
Yes, by enabling AI agents to call diverse backend functions, it supports complex, multi-step reasoning and workflows.
What AI models are compatible with AgentRPC?
AgentRPC supports OpenAI, Anthropic, LiteLLM, OpenRouter, and other models compatible with MCP and OpenAI tool definitions.