Scalable LLM Agent Tool Access in the Cloud
LLM agents increasingly rely on tool calling to act on external systems, and the Model Context Protocol (MCP) has quickly become its de facto interface. Operating MCP at cloud scale, however, becomes difficult. On the tool provider side, legacy services are not directly callable through MCP; the rapid protocol development also creates ongoing compatibility cost. On the agent side, the number of accessible tool is limited by the LLM context window and inference overhead; mounting a large tool set increases token usage and inference latency and can reduce task success rate. Moreover, for stateful MCP backends with multiple replicas, preserving session affinity increases client-side complexi...
| Authors | Mingxin Li, Enge Song, Yueshang Zuo et al. |
|---|---|
| Primary category | cs.DC |
| Published | 17 July 2026 |
| Last updated at source | 17 July 2026 |
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