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Glama
cyqlelabs

MCP Dual-Cycle Reasoner

by cyqlelabs

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
start_monitoringB

Start metacognitive monitoring of an agent's cognitive process

stop_monitoringA

Stop metacognitive monitoring and get session summary

process_trace_updateC

Process a cognitive trace update from the agent (main monitoring function)

detect_loopA

Detect if the agent is stuck in a loop using various strategies

store_experienceB

Store a case for future case-based reasoning

retrieve_similar_casesB

Retrieve similar cases from the case base

get_monitoring_statusA

Get current monitoring status and statistics

reset_engineA

Reset the dual-cycle engine state

configure_detectionB

Configure loop detection parameters and domain-specific progress indicators

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.6/5.0

Scored across 9 tools

Disambiguation4/5

Most tools have distinct purposes, but there is some potential overlap between 'detect_loop' and 'process_trace_update' as both involve monitoring cognitive processes. The descriptions clarify their roles, with 'detect_loop' focused on loop detection and 'process_trace_update' handling general trace updates, but an agent might occasionally confuse them in practice.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case, such as 'configure_detection', 'detect_loop', and 'start_monitoring'. This uniformity makes the set predictable and easy to navigate, with no deviations in naming conventions.

Tool Count5/5

With 9 tools, the count is well-scoped for a dual-cycle reasoner server, covering configuration, monitoring, detection, and case management. Each tool appears to serve a specific function without redundancy, making the set appropriately sized for the domain.

Completeness4/5

The tool set provides comprehensive coverage for metacognitive monitoring and reasoning, including start/stop, detection, status retrieval, and case storage. A minor gap exists in tools for modifying or deleting stored cases, but core workflows are well-supported, allowing agents to work around this limitation.

Maintenance

ActivityNo data
ResponsivenessNo issues