arXiv:2507.10593v3 Announce Type: replace-cross Abstract: Every LLM tool call is structurally an RPC -- a function name, JSON arguments, and a serialized result -- yet each protocol (native Python, MCP, OpenAPI, LangChain) is integrated from scratch. We present ToolRegistry, a system that makes this RPC nature explicit: a single Tool object acts as a universal stub regardless of transport, while the registry serves as the RPC client runtime for dispatch, schema generation, and execution. The system ships as three packages -- a core registry, a server exposing tools over MCP and OpenAPI, and a
The proliferation of various LLM tool integration protocols necessitates a unified approach for efficient development and deployment of agentic systems.
This development streamlines the integration of external functionalities with large language models, significantly accelerating the development and deployment of AI agents.
Developers can now manage LLM tool calls with a single, protocol-agnostic system, reducing fragmentation and complexity in AI agent infrastructure.
- · AI Agent Developers
- · LLM Platform Providers
- · Open-source AI Community
- · Companies with proprietary, highly fragmented tool integration solutions
Easier and faster development of complex AI agents capable of interacting with diverse external systems.
Increased adoption and interoperability among different LLM applications and tools, fostering broader ecosystem growth.
The acceleration of AI agent capabilities could lead to more rapid automation of white-collar tasks, impacting various industries.
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Read at arXiv cs.CL