mlsanityData to 14 Oct 2026

Empirical Comparison of Agent Communication Protocols for Task Orchestration

arXiv 2603.22823 ↗First posted 24 Mar 2026cs.AIcited by 1

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

Context. The problem of comparative evaluation of communication protocols for task orchestration by large language model (LLM) agents is considered. The object of study is the process of interaction between LLM agents and external tools, as well as between autonomous LLM agents, during task orchestration. Objective. The goal of this work is to develop a systematic pilot benchmark comparing tool integration, multi-agent dele-gation, and hybrid architectures for standardized queries at three levels of complexity, and to quantify the advantages and disadvantages in terms of response time, context window consumption, cost, error recovery, and implementation complexity.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 6 of its 19 references that are in the map. First posted on arXiv 24 Mar 2026.

Builds on

6 of 19 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework1 Aug

Other references · 5

  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. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
  4. 2023Gorilla: Large Language Model Connected with Massive APIscited by 1,332
  5. 2025A survey of agent interoperability protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP)cited by 101

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Protocol Compression Changes Which Party Pays: Bilateral Cost in Cross-Organization LLM Agent Communicationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026A Technical Taxonomy of LLM Agent Communication Protocols
  2. 2026Utility-Guided Agent Orchestration for Efficient LLM Tool Use
  3. 2024MARCO: Multi-Agent Real-time Chat Orchestration
  4. 2025Beyond Self-Talk: A Communication-Centric Survey of LLM-Based Multi-Agent Systems
  5. 2026The Evolution of Tool Use in LLM Agents: From Single-Tool Call to Multi-Tool Orchestration
  6. 2025LLMs Working in Harmony: A Survey on the Technological Aspects of Building Effective LLM-Based Multi Agent Systems
  7. 2026PerspectiveGap: A Benchmark for Multi-Agent Orchestration Prompting
  8. 2025Multi-Mission Tool Bench: Assessing the Robustness of LLM based Agents through Related and Dynamic Missions