HTN Planning as a Coordination Layer for Multi-Server MCP Tool Orchestration

Abstract:The Model Context Protocol (MCP) isolates servers by design: only the host can orchestrate cross-server workflows. When the host is a large language model, the resulting orchestrations are non-deterministic, non-reproducible, and pay one inference round-trip per tool call. We present a coordination architecture in which a Hierarchical Task Network (HTN) planner generates a verifiable cross-server plan once, and a runtime middleware executes it deterministically across multiple MCP servers, binding cross-action data dependencies via a template mechanism (\verb|${context.X}|) substituted at execution time. The architecture mirrors MCP's isolation constraint: each compound task decomposes into server-local primitive actions, and inter-server data flow is bound at execution time via JSON-path output extractors. We instantiate the architecture on five HTN domains spanning laboratory robotics, bioinformatics and multiscale modelling, and demonstrate end-to-end execution from a browser-based plan controller against eight live third-party MCP servers querying real biological databases.

5 pages. Camera-ready version of a paper accepted at the ICAPS 2026 Workshop on Hierarchical Planning (HPlan 2026), Dublin. Non-archival. Code: this https URL

Artificial Intelligence (cs.AI)

arXiv:2609.33731 [cs.AI]

(or arXiv:2609.33731v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2609.33731 arXiv-issued DOI via DataCite (pending registration)