cbt-mcp

# 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 prompts - **`socratic_dialogue`** - Progressive questioning to examine assumptions - **`generate_thought_experiment`** - Mental simulations for concept exploration - **`thinking_depth_ladder`** - Ascend through 7 levels of thinking depth - **`recursive_questioning`** - Questions that spiral into deeper understanding - **`expand_thought`** - Apply 10+ lenses to expand perspectives - **`metacognitive_check`** - Assess and improve thinking quality - **`thinking_session_summary`** - Get metrics and insights from thinking session ### Session Management - **`start_session`** - Initialize a CBT session with unique ID - **`get_session_summary`** - Get comprehensive session analysis with insights ### Core Interventions - **`analyze_stuck_pattern`** - Enhanced diagnosis with session tracking - **`reframe_thought`** - Cognitive distortion detection and targeted reframes - **`create_action_plan`** - Obstacle analysis with backup strategies - **`regulate_frustration`** - Level-based interventions with immediate relief - **`wellness_check`** - Wellness scoring with risk factor identification ## Setup ```bash # 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) ```python # 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 ```python # 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 1. **Cognitive Reframing** - Challenge negative patterns 2. **Thought Challenging** - Question distortions 3. **Problem Solving** - Systematic approach 4. **Behavioral Activation** - Break paralysis 5. **Mindfulness** - Present focus 6. **Socratic Questioning** - Uncover assumptions 7. **Cost-Benefit Analysis** - Evaluate trade-offs 8. **Graded Exposure** - Progressive steps 9. **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 ```bash # 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 1. **Surface**: Immediate, obvious responses 2. **Factual**: Evidence-based analysis 3. **Analytical**: Pattern recognition 4. **Critical**: Assumption questioning 5. **Synthetic**: Integration of perspectives 6. **Philosophical**: Fundamental principles 7. **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