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World Congress 2026 Europe • Jul 10, 2026 • Session details

Building APIs for Agents vs Systems. Is MCP the answer?

Adam Bird

Standard REST APIs will make your AI agents hallucinate. Learn how the Model Context Protocol (MCP) shifts orchestration to the server for a flawless agent experience.

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#1 about 3 min

Adapting web APIs for deterministic systems versus agents

Designing APIs for agents requires moving past composable REST primitives to deliver isolated outcomes directly.

#2 about 5 min

Managing complex workflows for unpredictable AI agent consumers

While REST relies on composable primitives, complex multi-step interactions cause drift and overwhelm non-deterministic models.

#3 about 2 min

Centralizing execution orchestration on the server using MCP

Managing state and workflows server-side prevents agents from failing complex operational sequences.

#4 about 3 min

Optimizing tool granularity and limiting multi-step automated processes

Reducing operations to a maximum of two procedural steps prevents exponential complexity loops and unexpected execution failures.

#5 about 2 min

Merging documentation and source code using MCP schemas

Defining parameters and intent inline guarantees that documentation perfectly mirrors the actual code structure.

#6 about 2 min

Designing error messages as actionable guides for agents

Replacing static status codes with descriptive, actionable error responses allows agents to unblock themselves and dynamically correct inputs.

#7 about 4 min

Delivering dynamic API footprints and schemas at runtime

Generating specific API capabilities based on runtime context eliminates backwards compatibility bloat and increases execution success rates.

#8 about 3 min

Implementing strict data filtering to maintain security boundaries

Restricting agent access to the minimum necessary application data prevents unpredictable data breaches and preserves customer trust.

#9 about 2 min

Building observability to verify unexpected AI agent behavior

Robust monitoring acts as an essential diagnostic tool when AI models hallucinate or falsely report API execution paths.

#10 about 3 min

Combining deterministic workflows with agent-based protocol automation models

Combining deterministic infrastructure with interaction protocols provides practical guardrails against unpredictable autonomous workflows.

#11 about 2 min

Constraining nested agent communication using domain-specific translation layers

Standardizing domain responsibilities via an intermediate protocol provides defined guardrails that prevent autonomous agents from triggering unintended chain reactions.

Matching moments

2:36 min

Core concepts and advantages of the Model Context Protocol

Rishabh Budhiraja Rishabh Budhiraja +1 · WWC Europe 2026

1:11 min

Treating AI tools as standard governed enterprise capabilities

Stefan Mesquita Stefan Mesquita · WWC Europe 2026

5:54 min

Standardizing agent interactions with the Web MCP proposal

Chris Heilmann +2 · LIVE

3:25 min

Understanding foundational concepts of LLMs, agents, and MCPs

Perf + AI

1:48 min

Defining true agent behavior versus traditional enterprise chatbots

Dennis Zielke Dennis Zielke +1 · WWC 2025

2:34 min

Balancing developer autonomy with the adoption of coding agents

Clemens Wasner Clemens Wasner +4 · WWC Europe 2026

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