mlsanityData to 14 Oct 2026

MCP Server Architecture Patterns for LLM-Integrated Applications

arXiv 2606.30317 ↗First posted 29 Jun 2026cs.SE cs.AIcited by 0

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

The Model Context Protocol (MCP), introduced by Anthropic in November 2024, defines a standardized interface for connecting large language models (LLMs) to external tools, data sources, and services. Within months of release, hundreds of community-built MCP servers appeared on GitHub, but no software-maintenance literature has yet described how the ecosystem is being structured in production. This industry experience paper catalogues five recurring MCP server architectural patterns observed across an enumerated corpus of fifteen independently developed servers (five production servers from the ANSYR voice AI platform plus ten public servers from the official MCP registry): Resource Gateway, Tool Orchestrator, Stateful Session Server, Proxy Aggregator, and Domain-Specific Adapter. Each pattern is described in the structured form of Gamma et al.: context, problem, solution, and consequences. We also document four anti-patterns and a set of cross-cutting concerns around authentication, versioning, and observability. The quantitative evaluation contributes three measurements: inter-rater reliability of the taxonomy across two independent LLM raters on 54 held-out servers (Cohen's kappa = 0.76), which also localizes three pattern-boundary ambiguities; transport overhead measured end-to-end on loopback and modeled for cross-host paths; and a tool-count study showing tool-selection accuracy drops below 90% between 10 and 15 tools per context for Claude Haiku 4.5 and between 20 and 30 tools for Sonnet 4. Code, corpus, and prompts are released as a replication package.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 7 of its 21 references that are in the map. First posted on arXiv 29 Jun 2026.

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7 of 21 references.

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  1. 2025A Measurement Study of Model Context Protocol Ecosystem29 Sep

Other references · 6

  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. 2025Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directionscited by 265
  4. 2025Model Context Protocol (MCP) at First Glance: Studying the Security and Maintainability of MCP Serverscited by 65
  5. 2025RAG-MCP: Mitigating Prompt Bloat in LLM Tool Selection via Retrieval-Augmented Generationcited by 28
  6. 2025LongFuncEval: Measuring the effectiveness of long context models for function callingcited by 18

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  1. 2025A Large-Scale Evolvable Dataset for Model Context Protocol Ecosystem and Security Analysis
  2. 2026Understanding How Enterprises Adopt the Model Context Protocol for LLM-Driven Software Engineering
  3. 2025MCP Safety Audit: LLMs with the Model Context Protocol Allow Major Security Exploits
  4. 2026Enhancing Model Context Protocol (MCP) with Context-Aware Server Collaboration
  5. 2026A Taxonomy of Runtime Faults in Model Context Protocol Servers
  6. 2025Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol (MCP) Ecosystem
  7. 2026An Empirical Study of Model Context Protocol Applications
  8. 2026Same Name, Different Server: A Security Census of Silent Drift in the Model Context Protocol Ecosystem