Session Buddy

A Session Management MCP Server for Claude Code

A dedicated MCP server that provides comprehensive session management functionality for Claude Code sessions across any project.

Features

• 🚀 Session Initialization: Complete setup with UV dependency management, project analysis, and automation tools

• 🔍 Quality Checkpoints: Mid-session quality monitoring with workflow analysis and optimization recommendations

• 🏁 Session Cleanup: Comprehensive cleanup with learning capture and handoff file creation

• 📊 Status Monitoring: Real-time session status and project context analysis

• ⚡ Auto-Generated Shortcuts: Automatically creates /start, /checkpoint, and /end Claude Code slash commands

🚀 Automatic Session Management (NEW!)

For Git Repositories:

• ✅ Automatic initialization when Claude Code connects

• ✅ Automatic cleanup when session ends (quit, crash, or network failure)

• ✅ Intelligent auto-compaction during checkpoints

• ✅ Zero manual intervention required

For Non-Git Projects:

• 📝 Use /start for manual initialization

• 📝 Use /end for manual cleanup

• 📝 Full session management features available on-demand

The server automatically detects git repositories and provides seamless session lifecycle management with crash resilience and network failure recovery. Non-git projects retain manual control for flexible workflow management.

Available MCP Tools

This server provides 79+ specialized tools organized into 11 functional categories. For a complete list of tools, see the MCP Tools Reference.

Core Session Management:

• start - Comprehensive session initialization with project analysis and memory setup

• checkpoint - Mid-session quality assessment with workflow analysis

• end - Complete session cleanup with learning capture

• status - Current session overview with health checks

Memory & Conversation Search:

• store_reflection - Store insights with tagging and embeddings

• quick_search - Fast overview search with count and top results

• search_summary - Aggregated insights without individual result details

• get_more_results - Pagination support for large result sets

• search_by_file - Find conversations tied to a specific file

• search_by_concept - Semantic search by concept with optional file context

Knowledge Graph (DuckPGQ):

• Entity and relationship management for project knowledge

• SQL/PGQ graph queries for complex relationship analysis

• See Knowledge Graph Integration Guide

All tools use local processing for privacy, with DuckDB vector storage (FLOAT[384] embeddings) and ONNX-based semantic search requiring no external API calls.

🚀 Integration with Crackerjack

Session Buddy includes deep integration with Crackerjack, the AI-driven Python development platform:

Key Features:

• 📊 Quality Metrics Tracking: Automatically captures and tracks quality scores over time

• 🧪 Test Result Monitoring: Learns from test patterns, failures, and successful fixes

• 🔍 Error Pattern Recognition: Remembers how specific errors were resolved and suggests solutions

Example Workflow:

1. 🚀 Session Buddy - Sets up your session with accumulated context from previous work

2. 🔧 Crackerjack runs quality checks and applies AI agent fixes to resolve issues

3. 💾 Session Buddy captures successful patterns and error resolutions

4. 🧠 Next session starts with all accumulated knowledge

For detailed information on Crackerjack integration, see Crackerjack Integration Guide.

Installation

From Source

MCP Configuration

Add to your project's .mcp.json file:

Alternative: Use Script Entry Point

If installed with pip/uv, you can use the script entry point:

Dependencies: Requires Python 3.13+. For a complete list of dependencies, see pyproject.toml. Recent changes include upgrading FastAPI to the 0.127+ series for improved compatibility and removing sitecustomize.py for faster startup reliability.

🧠 Setting Up Semantic Search (Optional)

Session Buddy includes semantic search capabilities using local AI embeddings with no external API dependencies.

Current Status:

• ✅ Text Search: Works out of the box (fast, keyword-based)

• ✅ Semantic Search: Works with ONNX model (no PyTorch required!)

For Text Search (Default): No additional setup needed! The system uses full-text search with FTS5 for fast, accurate results.

For Semantic Search (Optional):

The system uses pre-converted ONNX models for efficient semantic search without requiring PyTorch:

This downloads the Xenova/all-MiniLM-L6-v2 model (~100MB) which includes:

• Pre-converted ONNX model (no PyTorch needed!)

• 384-dimensional embeddings for semantic similarity

• Fast CPU inference with ONNX Runtime

Note: Text search is highly effective and recommended for most use cases. Semantic search provides enhanced conceptual matching by understanding meaning beyond keywords.

Usage

Once configured, the following slash commands become available in Claude Code:

Primary Session Commands:

• /session-buddy:start - Full session initialization

• /session-buddy:checkpoint - Quality monitoring checkpoint with scoring

• /session-buddy:end - Complete session cleanup with learning capture

• /session-buddy:status - Current status overview with health checks

Auto-Generated Shortcuts: After running /session-buddy:start once, these shortcuts are automatically created:

• /start → /session-buddy:start

• /checkpoint [name] → /session-buddy:checkpoint

• /end → /session-buddy:end

These shortcuts are created in ~/.claude/commands/ and work across all projects

Memory & Search Commands:

• /session-buddy:quick_search - Fast search with overview results

• /session-buddy:search_summary - Aggregated insights without full result lists

• /session-buddy:get_more_results - Paginate search results

• /session-buddy:search_by_file - Find results tied to a specific file

• /session-buddy:search_by_concept - Semantic search by concept

• /session-buddy:search_code - Search code-related conversations

• /session-buddy:search_errors - Search error and failure discussions

• /session-buddy:search_temporal - Search using time expressions

• /session-buddy:store_reflection - Store important insights with tagging

• /session-buddy:reflection_stats - Stats about the reflection database

For running the server directly in development mode:

Memory System

Built-in Conversation Memory:

• Local Storage: DuckDB database at ~/.claude/data/reflection.duckdb

• Embeddings: Local ONNX models for semantic search (no external API needed)

• Privacy: Everything runs locally with no external dependencies

• Cross-Project: Conversations tagged by project context for organized retrieval

Search Capabilities:

• Semantic Search: Vector similarity matching with customizable thresholds

• Time Decay: Recent conversations prioritized in results

• Filtering: Search by project context or across all projects

Data Storage

This server manages its data locally in the user's home directory:

• Memory Storage: ~/.claude/data/reflection.duckdb

• Session Logs: ~/.claude/logs/

• Configuration: Uses pyproject.toml and environment variables

Recommended Session Workflow

1. Initialize Session: /session-buddy:start - Sets up project context, dependencies, and memory system

2. Monitor Progress: /session-buddy:checkpoint (every 30-45 minutes) - Quality scoring and optimization

3. Search Past Work: /session-buddy:quick_search or /session-buddy:search_summary - Find relevant past conversations and solutions

4. Store Important Insights: /session-buddy:store_reflection - Capture key learnings for future sessions

5. End Session: /session-buddy:end - Final assessment, learning capture, and cleanup

Benefits

Comprehensive Coverage

• Session Quality: Real-time monitoring and optimization

• Memory Persistence: Cross-session conversation retention

• Project Structure: Context-aware development workflows

Reduced Friction

• Single Command Setup: One /session-buddy:start sets up everything

• Local Dependencies: No external API calls or services required

• Intelligent Permissions: Reduces repeated permission prompts

• Automated Workflows: Structured processes for common tasks

Enhanced Productivity

• Quality Scoring: Guides session effectiveness

• Built-in Memory: Enables building on past work automatically

• Project Templates: Accelerates development setup

• Knowledge Persistence: Maintains context across sessions

Documentation

Complete documentation is available in the docs/ directory:

• User Documentation - Quick start, configuration, and deployment guides

• Developer Documentation - Architecture, testing, and integration guides

• Feature Guides - AI integration, token optimization, and other features

• Reference - MCP schemas and command references

Troubleshooting

Common Issues:

• Memory/embedding issues: Ensure all dependencies are installed with uv sync

• Path errors: Verify cwd and PYTHONPATH are set correctly in .mcp.json

• Permission issues: Remove ~/.claude/sessions/trusted_permissions.json to reset trusted operations

Debug Mode:

For more detailed troubleshooting guidance, see Configuration Guide or Quick Start Guide.