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📚Complete Guide

AgentRPC Tutorial: Get Started in 5 Minutes [2026]

Master AgentRPC with our step-by-step tutorial, detailed feature walkthrough, and expert tips.

Get Started with AgentRPC →Full Review ↗
🚀

Getting Started with AgentRPC

1

Sign Up and Install Create an account at agentrpc.com and install the AgentRPC SDK using npm or pip. The installation includes CLI tools and development libraries. ##

2

Initialize Your Project Run 'agentrpc init' to create a new project with sample agent configurations. Choose from templates for common use cases like customer service or workflow automation. ##

3

Define Your Agents Create agent definitions using the AgentRPC schema. Define capabilities, communication protocols, and dependencies between agents. ##

4

Set Up Communication Channels Configure RPC channels between your agents using the built

5

in networking layer. AgentRPC handles serialization, routing, and error handling automatically. ##

6

Deploy and Monitor Deploy your agent network using the AgentRPC runtime. Use the web dashboard to monitor agent communication and performance in real

7

Scale Your System Add new agents or scale existing ones using the auto

8

scaling features. AgentRPC automatically handles load balancing and resource allocation.

💡 Quick Start: Follow these 8 steps in order to get up and running with AgentRPC quickly.

❓ Frequently Asked Questions

How is AgentRPC different from regular RPC frameworks like gRPC?

AgentRPC is designed for AI agent workflows. It handles long-running functions beyond HTTP timeout limits, integrates natively with MCP and OpenAI-compatible SDKs, and works across private networks without port configuration. gRPC requires both endpoints to be network-accessible to each other, which doesn't work for agents calling functions behind firewalls.

Do I need AgentRPC if my tools are on public APIs?

No. AgentRPC adds value only when network boundaries prevent direct function calls. If your tools are publicly accessible, standard HTTP calls or local MCP servers work fine without the extra layer.

What's the latency overhead?

The hosted RPC server adds a network hop. For functions that complete in milliseconds, this is noticeable (tens of ms added). For typical agent tasks that take seconds or minutes — database queries, report generation, API chains — the overhead is negligible relative to function execution time.

Is AgentRPC open-source?

Yes. The SDKs and core components are open-source under the Apache 2.0 license on GitHub. The hosted RPC server at api.agentrpc.com is a managed service for routing, health monitoring, and observability. You can self-host the SDKs and point to your own server if needed.

How does AgentRPC compare to Temporal for long-running workflows?

Temporal is a general-purpose workflow orchestration engine with state management, retries, and complex workflow graphs. AgentRPC is simpler and purpose-built for the specific problem of AI agents calling functions across network boundaries. If you need full workflow orchestration, use Temporal. If you just need agents to reach private functions, AgentRPC is lighter weight.

🎯

Ready to Get Started?

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Tutorial updated March 2026