by agentrpc
AgentRPC is a universal RPC layer for AI agents, enabling seamless connection to any function, language, or framework in
AgentRPC provides a universal RPC layer that lets AI agents call functions across different languages and private networks. It wraps your functions and exposes them through MCP and OpenAI-compatible tool interfaces.
AgentRPC is an official MCP server published by agentrpc that provides AI assistants with tools and capabilities via the Model Context Protocol. AgentRPC is a universal RPC layer for AI agents, enabling seamless connection to any function, language, or framework in It is categorized under ai ml, developer tools.
You can install AgentRPC in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
Apache-2.0
AgentRPC is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
We wired AgentRPC into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Useful MCP listing: AgentRPC is the kind of server we cite when onboarding engineers to host + tool permissions.
Strong directory entry: AgentRPC surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We evaluated AgentRPC against two servers with overlapping tools; this profile had the clearer scope statement.
AgentRPC is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
AgentRPC has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
AgentRPC reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Strong directory entry: AgentRPC surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Useful MCP listing: AgentRPC is the kind of server we cite when onboarding engineers to host + tool permissions.
We wired AgentRPC into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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Universal RPC layer for AI agents across network boundaries and languages
AgentRPC allows you to connect to any function, in any language, across network boundaries. It's ideal when you have services deployed in:
AgentRPC wraps your functions in a universal RPC interface, connecting them to a hosted RPC server accessible through open standards:
| 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 |
Follow the quick start example on our docs site.
Explore working examples in the examples directory.
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.
Add to your claude_desktop_config.json:
{
"mcpServers": {
"agentrpc": {
"command": "npx",
"args": [
"-y",
"agentrpc",
"mcp"
],
"env": {
"AGENTRPC_API_SECRET": "<YOUR_API_SECRET>"
}
}
}
}
Add to your ~/.cursor/mcp.json:
{
"mcpServers": {
"agentrpc": {
"command": "npx",
"args": ["-y", "agentrpc", "mcp"],
"env": {
"AGENTRPC_API_SECRET": "<YOUR_API_SECRET>"
}
}
}
}
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.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.