Dual Cycle Reasoner
@cyqlelabs
About Dual Cycle Reasoner
A Model Context Protocol (MCP) server implementing the Dual-Cycle Metacognitive Reasoning Framework for autonomous agents. This tool empowers agents with greater self-awareness and reliability through intelligent loop detection and experience acquisition.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"dual-cycle-reasoner": {
"command": "npx",
"args": [
"@cyqlelabs/mcp-dual-cycle-reasoner"
]
}
}
}Tools
No tools detected
Fetch the live tool list by running this server in a temporary sandbox using the button above.
Overview
What is Dual Cycle Reasoner?
Dual Cycle Reasoner is an MCP server that implements a Dual-Cycle Metacognitive Reasoning Framework for autonomous agents. It enables agents to monitor their own cognitive processes, detect repetitive loops, and learn from past experiences to improve decision-making.
How to use Dual Cycle Reasoner?
Install the package and run the server via HTTP Stream (default on port 8080) or stdio transport. Configure it in Claude Desktop by adding the @cyqlelabs/mcp-dual-cycle-reasoner package to the MCP servers configuration. Use tools like start_monitoring, process_trace_update, detect_loop, store_experience, and retrieve_similar_cases to monitor agents and manage experiences.
Key features of Dual Cycle Reasoner
- Entropy-based anomaly detection with statistical analysis
- Semantic similarity matching and NLI-based text analysis
- Multi-strategy loop detection (statistical, pattern, hybrid)
- Time series trend and cyclical pattern recognition
- Configurable domain-specific thresholds and progress indicators
- Intelligent case management with quality scoring and deduplication
Use cases of Dual Cycle Reasoner
- Monitoring autonomous web agents to detect repetitive action loops
- Storing and retrieving solutions for recurring task failures
- Configuring detection parameters for specific domains like form filling
- Analyzing agent behavior trends over multiple sessions
- Improving agent reliability through experience-based recovery
FAQ from Dual Cycle Reasoner
What runtime dependencies does Dual Cycle Reasoner require?
Node.js and TypeScript, with libraries including simple-statistics, natural, compromise, and HuggingFace Transformers for NLP and machine learning.
What transport protocols does Dual Cycle Reasoner support?
It supports SSE (HTTP Stream) on port 8080 by default, and stdio transport when started with the --stdio flag.
Where does Dual Cycle Reasoner store case data?
Case data is stored in memory during a session; no persistent storage is mentioned in the documentation.
Does Dual Cycle Reasoner require authentication?
No authentication mechanism is described; the server operates without built-in auth.
What are the known limits of Dual Cycle Reasoner?
No specific limits are documented; the server is designed for agent monitoring and case-based reasoning in autonomous systems.
Frequently asked questions
What runtime dependencies does Dual Cycle Reasoner require?
Node.js and TypeScript, with libraries including `simple-statistics`, `natural`, `compromise`, and HuggingFace Transformers for NLP and machine learning.
What transport protocols does Dual Cycle Reasoner support?
It supports SSE (HTTP Stream) on port 8080 by default, and stdio transport when started with the `--stdio` flag.
Where does Dual Cycle Reasoner store case data?
Case data is stored in memory during a session; no persistent storage is mentioned in the documentation.
Does Dual Cycle Reasoner require authentication?
No authentication mechanism is described; the server operates without built-in auth.
What are the known limits of Dual Cycle Reasoner?
No specific limits are documented; the server is designed for agent monitoring and case-based reasoning in autonomous systems.
Basic information
More Other MCP servers
Inbox Zero AI
elie222The world's best AI personal assistant for email. Open source app to help you reach inbox zero fast.
🪟 Windows-MCP
CursorTouchMCP Server for Computer Use in Windows
MCP Go 🚀
mark3labsA Go implementation of the Model Context Protocol (MCP), enabling seamless integration between LLM applications and external data sources and tools.
Codelf
unbugA search tool helps dev to solve the naming things problem.

DeepMark
DeepMark helps teachers deliver rapid, consistent marking with meaningful feedback for every student — in a fraction of the time. What once took a week, now takes one free period.
Comments