cyqlelabs/mcp-dual-cycle-reasoner

A MCP server implementing the Dual-Cycle Metacognitive Reasoning Framework for autonomous agents. A loop prevention and experience recall mechanism.

46
/ 100
Emerging

This tool helps autonomous AI agents avoid getting stuck in repetitive loops and learn from past experiences. It takes in an agent's actions and current goal, monitors its progress, and alerts if it detects the agent is repeating itself. The output tells the agent when it needs to change its approach or suggests solutions from similar past problems. This is for developers building and deploying advanced AI agents who need them to be more reliable and self-aware.

No commits in the last 6 months. Available on npm.

Use this if you are developing AI agents and need a mechanism to prevent them from endlessly repeating actions or getting stuck, while also enabling them to recall and apply solutions from previous successful interactions.

Not ideal if your AI agent's tasks are simple and linear, or if you do not require advanced self-monitoring and experience-based decision-making capabilities.

AI Agent Development Autonomous Systems Agent Reliability Cognitive Robotics Reinforcement Learning
Stale 6m
Maintenance 2 / 25
Adoption 5 / 25
Maturity 24 / 25
Community 15 / 25

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Stars

10

Forks

4

Language

TypeScript

License

MIT

Last pushed

Sep 18, 2025

Commits (30d)

0

Dependencies

10

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