implementation

Integrate MCP Tools & Adaptive Thinking

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Linked challenge: Build MCP-Enabled Social Media Policy Enforcement Agents

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Linked challenge

Build MCP-Enabled Social Media Policy Enforcement Agents

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Integrate MCP into your agents to allow them to access external 'enterprise policy databases' (simulated JSON files or simple API endpoints) and 'social media feeds' (synthetic data). Implement the adaptive thinking budget mechanism, where agents can decide to 'deep dive' or 'quick scan' based on initial assessments of content sensitivity or policy relevance.

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Hold the task contract and output shape stable so generated implementations remain comparable.

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Update libraries, interfaces, and environment assumptions to match the stack you actually run.

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Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.

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implementation

This prompt is mostly narrative and instruction-driven, so adapt examples and output constraints before you rewrite the structure.

Linked challenge

Build MCP-Enabled Social Media Policy Enforcement Agents

Companies are increasing social media monitoring due to reputational risks from employee posts. This challenge involves building an advanced multi-agent system that autonomously monitors public social media feeds for potential employee policy violations. The system will leverage a graph-based workflow to analyze content, interpret company policies (retrieved via RAG), and flag potential issues, while adapting its reasoning budget based on the sensitivity of the content or the severity of the potential violation. You will design and implement a sophisticated LangGraph-based agent network where a 'Monitor Agent' feeds data to a 'Policy Interpretation Agent' and a 'Risk Assessment Agent'. These agents will communicate using a defined protocol, integrating with external enterprise policy databases via MCP for real-time policy lookup and dynamically adjusting their processing depth (thinking budget) to balance efficiency and accuracy. The system must provide actionable insights and prioritize alerts for human review, ensuring compliance while minimizing false positives.

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