AgentRPC
A universal RPC layer for AI agents. Connect to any function, any language, across network boundaries. AgentRPC wraps your functions in a universal RPC interface, connecting them to a hosted server accessible through open standards including MCP.
What is AgentRPC?
what is AgentRPC? AgentRPC is a universal RPC layer designed for AI agents, enabling connections to any function across different programming languages and network boundaries. how to use AgentRPC? To use AgentRPC, obtain an API key, choose your preferred SDK (Go, Node.js, or Python), and register your functions using the provided SDKs. You can also set up an MCP server for external AI models to interact with your registered tools. key features of AgentRPC? Multi-language support for TypeScript, Go, Python, and .NET (coming soon) Private network support without the need for open ports Long-running function support with long polling SDKs Full observability with tracing, metrics, and events Automatic failover and retries for enhanced reliability Compatibility with MCP and OpenAI SDKs use cases of AgentRPC? Connecting AI models deployed in private VPCs. Integrating various services across multiple cloud environments. Enabling long-running function calls beyond HTTP timeout limits. FAQ from AgentRPC? What programming languages does AgentRPC support? AgentRPC supports TypeScript, Go, Python, and .NET (coming soon). Is there a cost to use AgentRPC? AgentRPC offers a free tier, but check the website for detailed pricing. How do I monitor the health of my functions? AgentRPC provides comprehensive tracing and metrics for full observability.
As an MCP (Model Context Protocol) server, AgentRPC enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.
How to use AgentRPC
To use AgentRPC, obtain an API key, choose your preferred SDK (Go, Node.js, or Python), and register your functions using the provided SDKs. You can also set up an MCP server for external AI models to interact with your registered tools. key features of AgentRPC? Multi-language support for TypeScript, Go, Python, and .NET (coming soon) Private network support without the need for open ports Long-running function support with long polling SDKs Full observability with tracing, metrics, and events Automatic failover and retries for enhanced reliability Compatibility with MCP and OpenAI SDKs use cases of AgentRPC? Connecting AI models deployed in private VPCs. Integrating various services across multiple cloud environments. Enabling long-running function calls beyond HTTP timeout limits. FAQ from AgentRPC? What programming languages does AgentRPC support? AgentRPC supports TypeScript, Go, Python, and .NET (coming soon). Is there a cost to use AgentRPC? AgentRPC offers a free tier, but check the website for detailed pricing. How do I monitor the health of my functions? AgentRPC provides comprehensive tracing and metrics for full observability.
Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.
Use Cases for this MCP Server
- No use cases specified.
MCP servers like AgentRPC can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.
About Model Context Protocol (MCP)
The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like AgentRPC provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.
Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.