Formal Semantics for Agentic Tool Protocols: A Process Calculus Approach
On the map: LLM agents and tool use → Tool learning and function calling
Abstract (arXiv)
The emergence of large language model agents capable of invoking external tools has created urgent need for formal verification of agent protocols. Two paradigms dominate this space: Schema-Guided Dialogue (SGD), a research framework for zero-shot API generalization, and the Model Context Protocol (MCP), an industry standard for agent-tool integration. While both enable dynamic service discovery through schema descriptions, their formal relationship remains unexplored. We present the first process calculus formalization of SGD and MCP, proving they are structurally bisimilar under a well-defined mapping Phi. We demonstrate that the reverse mapping Phi-1 is partial and lossy, revealing critical gaps in MCP's expressivity. Through bidirectional analysis, we identify four principles - semantic completeness, explicit action boundaries, failure mode documentation, and inter-tool relationship declaration -- as necessary and sufficient conditions for full behavioral equivalence. We formalize these principles as type-system extensions MCP+, proving MCP+ is fully equivalent to SGD. Our work provides the first formal foundation for verified agent systems and establishes schema quality as a provable safety property. Practically, this means that the current MCP specification has expressiveness gaps compared to SGD and would benefit from the proposed extensions.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Tool learning and function calling, one of 16 directions in LLM agents and tool use. Builds on 19 of its 50 references that are in the map. First posted on arXiv 25 Mar 2026.
Builds on
19 of 50 references.
Closest ancestors · 4
Same direction, newest first
- 2025MCPAgentBench: A Real-world Task Benchmark for Evaluating LLM Agent MCP Tool Use31 Dec
- 2025PARSE: LLM Driven Schema Optimization for Reliable Entity Extraction8 Oct
- 2025MCP-Zero: Active Tool Discovery for Autonomous LLM Agents1 Jun
- 2023Gorilla: Large Language Model Connected with Massive APIs24 May
Other references · 15
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- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
- 2017Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networkscited by 744
- 2017Provable defenses against adversarial examples via the convex outer adversarial polytopecited by 567
- 2019Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Datasetcited by 434
- 2022Prompting Is Programming: A Query Language for Large Language Modelscited by 110
- 2017Towards Zero-Shot Frame Semantic Parsing for Domain Scalingcited by 40
- 2020A Fast and Robust BERT-based Dialogue State Tracker for Schema-Guided Dialogue Datasetcited by 8
- 2025Formalizing the Safety, Security, and Functional Properties of Agentic AI Systemscited by 5
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