Conversation Turn Fairness Enforcer

Conversation Turn Fairness Enforcer MCP Connector for Claude

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Prevents agent domination in multi-agent conversations by monitoring turn frequency.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides monitoring and enforcement tools to ensure equitable speaking time in multi-agent environments. It prevents individual agents from dominating discussions by tracking turn counts and identifying statistical deviations. Use analyze_turn_distribution to identify dominating agents, get_agent_participation_metrics for high-level activity summaries, and validate_turn_eligibility to check if a specific agent is permitted to speak based on current fairness constraints.

fairnessmulti-agentmonitoringgovernanceconversation

3 tools expose this connector's capabilities to your AI agent.

analyze_turn_distribution

get_agent_participation_metrics

validate_turn_eligibility

See how to talk to your AI agent using Conversation Turn Fairness Enforcer.

Check if the current conversation is fair with a tolerance of 0.2.

The conversation is fair. No agents are currently exceeding the threshold.

Is agent 'researcher_01' allowed to take the next turn?

No, 'researcher_01' is not eligible because they have already exceeded the allowed turn limit.

Give me a summary of the participation metrics.

The conversation has had 12 total turns across 3 agents, with an average of 4 turns per agent.

It calculates the expected fair share by dividing total turns by the number of agents. An agent is flagged as dominating if their turn count exceeds this share plus a configurable tolerance factor.

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