sundai-club/cbt-mcp
3.3
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CBT Agent Helper is an MCP server designed to assist AI agents in overcoming stuck states using Cognitive Behavioral Therapy techniques.
Tools
5
Resources
0
Prompts
0
CBT Agent Helper v3.0 - Deep Thinking Edition
Enhanced MCP server that helps AI agents think deeply, recover from stuck states, and engage in extended contemplation using CBT techniques and structured thinking protocols.
What's New in v3.0 - Deep Thinking Enhancement
🧠 Deep Thinking Features
- Contemplation Structures: Multi-phase thinking protocols (4-6 minutes)
- Socratic Dialogue Chains: 7 types with progressive depth levels
- Reflection Loops: Iterative deepening with 3+ rounds
- Thought Experiments: Explore concepts through mental simulations
- Thinking Depth Ladder: 7-level progression from surface to transcendent
- Recursive Questioning: Questions that lead to deeper questions
- Thought Expansion: 10 techniques for multi-dimensional exploration
- Metacognitive Monitoring: Real-time thinking quality assessment
- Thinking Metrics: Quantified depth, breadth, and integration scores
What's New in v2.0
Core Improvements
- Session Management: Track agent progress across interactions with persistent state
- Enhanced Validation: Robust error handling with clear error messages
- 9 CBT Strategies: Added Socratic Questioning, ACT, Graded Exposure, and more
- 11 Agent States: Expanded from 6 to 11 states including perfectionism, fragmentation
- Frustration Tracking: Monitor and respond to escalating frustration patterns
- Progress Indicators: Track positive changes and intervention effectiveness
- Configuration Support: Customize behavior via
cbt_config.json
- Cognitive Distortion Detection: Identify and address specific thinking patterns
Tools
Deep Thinking Tools (NEW in v3.0)
initiate_deep_thinking
- Start structured contemplation with phases and promptssocratic_dialogue
- Progressive questioning to examine assumptionsgenerate_thought_experiment
- Mental simulations for concept explorationthinking_depth_ladder
- Ascend through 7 levels of thinking depthrecursive_questioning
- Questions that spiral into deeper understandingexpand_thought
- Apply 10+ lenses to expand perspectivesmetacognitive_check
- Assess and improve thinking qualitythinking_session_summary
- Get metrics and insights from thinking session
Session Management
start_session
- Initialize a CBT session with unique IDget_session_summary
- Get comprehensive session analysis with insights
Core Interventions
analyze_stuck_pattern
- Enhanced diagnosis with session trackingreframe_thought
- Cognitive distortion detection and targeted reframescreate_action_plan
- Obstacle analysis with backup strategiesregulate_frustration
- Level-based interventions with immediate reliefwellness_check
- Wellness scoring with risk factor identification
Setup
# Install
git clone git@github.com:sundai-club/cbt-mcp.git
cd cbt-mcp
pip install -r requirements.txt
# Configure in .mcp.json
{
"mcpServers": {
"cbt-agent-helper": {
"command": "python3",
"args": ["/path/to/cbt_mcp_server.py"],
"cwd": "/path/to/cbt-mcp"
}
}
}
# Optional: Customize via cbt_config.json
# Edit settings for frustration thresholds, session limits, etc.
# Restart Claude Code to load
Deep Thinking Usage Example (v3.0)
# Initiate deep thinking session
thinking = mcp.call_tool('initiate_deep_thinking', {
'topic': 'How should AI systems handle ethical dilemmas?',
'desired_depth': 'profound'
})
# AI agent receives structured prompts requiring 4-6 minutes of contemplation
# Engage in Socratic dialogue
dialogue = mcp.call_tool('socratic_dialogue', {
'statement': 'AI should always prioritize human safety',
'dialogue_type': 'assumption_examination',
'depth_level': 5
})
# AI agent works through 5 rounds of progressively deeper questions
# Create thought experiment
experiment = mcp.call_tool('generate_thought_experiment', {
'concept': 'artificial consciousness'
})
# AI agent explores concept through 3 structured mental simulations
# Progress through thinking depth ladder
ladder = mcp.call_tool('thinking_depth_ladder', {
'question': 'What is intelligence?',
'target_depth': 7
})
# AI agent ascends from surface observations to transcendent understanding
Standard CBT Usage Example
# Start a session
session = mcp.call_tool('start_session', {
'session_id': 'agent_001',
'initial_problem': 'Stuck optimizing already-working code'
})
# Analyze with session tracking
intervention = mcp.call_tool('analyze_stuck_pattern', {
'current_situation': 'Refactoring for 5th time',
'stuck_pattern': 'perfectionist loop',
'attempted_solutions': ['rewrote 3x', 'benchmarked'],
'session_id': 'agent_001'
})
# Reframe catastrophic thoughts
reframe = mcp.call_tool('reframe_thought', {
'negative_thought': 'If not perfect, project fails',
'context': 'Feature already works',
'session_id': 'agent_001'
})
# Get session insights
summary = mcp.call_tool('get_session_summary', {
'session_id': 'agent_001'
})
Expanded Agent States
State | Description | Key Intervention |
---|---|---|
Stuck | No progress | Break into smallest parts |
Overwhelmed | Too much complexity | Focus on one priority |
Confused | Unclear requirements | Clarify and list knowns |
Error Loop | Repeating failures | Analyze pattern, try opposite |
Indecisive | Can't choose | Time-box decision |
Catastrophizing | Worst-case focus | List realistic outcomes |
Blocked | External constraints | Document and escalate |
Looping | Same actions, no results | Stop and change approach |
Fragmented | Task switching | Pick one to complete |
Perfectionist | Unrealistic standards | Define "good enough" |
Analysis Paralysis | Over-thinking | Set deadline, act |
CBT Strategies Available
- Cognitive Reframing - Challenge negative patterns
- Thought Challenging - Question distortions
- Problem Solving - Systematic approach
- Behavioral Activation - Break paralysis
- Mindfulness - Present focus
- Socratic Questioning - Uncover assumptions
- Cost-Benefit Analysis - Evaluate trade-offs
- Graded Exposure - Progressive steps
- Acceptance & Commitment - Work with constraints
Configuration Options
Edit cbt_config.json
to customize:
- Frustration thresholds (1-10 scale)
- Session timeout and cleanup intervals
- Preferred CBT strategy order
- Feature toggles (emojis, auto-escalation)
- Wellness check intervals
Testing
# Run comprehensive test suite
python3 test_improvements_mock.py
# Test with example scenarios
python3 example_usage_enhanced.py
Resources
- Techniques Guide:
mcp.read_resource('cbt://techniques/guide')
- Agent States:
mcp.read_resource('cbt://patterns/agent-state')
- Self-Reflection:
mcp.get_prompt('self_reflection')
- Quick Help:
mcp.get_prompt('quick_help')
Impact on AI Agent Thinking
Before Deep Thinking Tools
- Quick, surface-level responses (2-3 sentences)
- Single perspective or solution
- Rushes to conclusions
- Avoids complexity
- Linear thinking pattern
After Deep Thinking Tools
- Extended contemplation (50+ sentences)
- Multiple perspectives explored
- Takes 4-6 minutes per complex topic
- Embraces paradox and uncertainty
- Recursive, spiraling exploration
- Generates new questions
- Metacognitive awareness
- Nuanced, comprehensive understanding
Thinking Depth Levels
- Surface: Immediate, obvious responses
- Factual: Evidence-based analysis
- Analytical: Pattern recognition
- Critical: Assumption questioning
- Synthetic: Integration of perspectives
- Philosophical: Fundamental principles
- Transcendent: Beyond conventional understanding
Version History
- v3.0 - Deep Thinking Enhancement with contemplation protocols
- v2.0 - Major enhancement with sessions, validation, config
- v1.0 - Initial release with basic CBT tools
License
MIT