mlsanityData to 14 Oct 2026

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

arXiv 2609.33731 ↗First posted 27 Sep 2026cs.AIcited by 0

New in LLM agents and tool use; no direction yet. LLM agents and tool use

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 21 references that are in the map. First posted on arXiv 27 Sep 2026.

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References · 8

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  2. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  3. 2023LLM+P: Empowering Large Language Models with Optimal Planning Proficiencycited by 501
  4. 2024Understanding the planning of LLM agents: A surveycited by 421
  5. 2023On the Planning Abilities of Large Language Models : A Critical Investigationcited by 312
  6. 2023An LLM Compiler for Parallel Function Callingcited by 179
  7. 2025ChatHTN: Interleaving Approximate (LLM) and Symbolic HTN Planningcited by 7
  8. 2026From Tool Orchestration to Code Execution: A Study of MCP Design Choicescited by 3

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  2. 2025MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers
  3. 2025ETOM: A Five-Level Benchmark for Evaluating Tool Orchestration within the MCP Ecosystem
  4. 2026MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers
  5. 2026Separating Intelligence from Execution: A Workflow Engine for the Model Context Protocol
  6. 2026Enhancing Model Context Protocol (MCP) with Context-Aware Server Collaboration
  7. 2025LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?
  8. 2025MCP-Flow: Facilitating LLM Agents to Master Real-World, Diverse and Scaling MCP Tools