ContextKeeper

Provides perfect memory for AI-assisted development by capturing project context snapshots, enabling natural language search, evolution tracking, and code intelligence.

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ContextKeeper 🧠

The Model Context Protocol (MCP) server with perfect memory for AI-assisted development

.NET 9 MCP Compatible Native AOT Tests License: MIT

ContextKeeper revolutionizes AI-assisted development by solving the fundamental problem of context loss between sessions. Using an LSM-tree inspired architecture, it maintains a complete, searchable history of your project's evolution—ensuring your AI assistant never forgets.

🌟 Key Features

📸 Comprehensive Context Capture

  • Development Snapshots: Capture complete project state including git context, workspace info, and documentation
  • Automatic Triggers: Git hooks (pre-commit, post-checkout) capture context automatically
  • Smart Archiving: LSM-tree inspired compaction keeps storage efficient while preserving history
  • Milestone Tracking: Tag snapshots with meaningful milestones for easy reference

🤖 AI-Native Design

  • Natural Language Search: Ask "when did we add authentication?" and get instant answers
  • Evolution Insights: Track how components evolved from "Planned" to "Completed"
  • Context-Aware Analysis: Intelligent keyword extraction and recommendations
  • Perfect Memory: Your AI assistant remembers everything across sessions

🔧 Model Context Protocol (MCP) Tools

Six powerful tools for AI assistants:

  • snapshot - Create comprehensive context snapshots
  • search_evolution - Natural language search through project history
  • track_component - Follow feature evolution over time
  • compare_snapshots - Diff any two snapshots
  • get_status - System status with compaction insights
  • get_timeline - Chronological project evolution view

💻 C# Code Intelligence

Five Roslyn-powered code analysis tools:

  • FindSymbolDefinitions - Locate symbol declarations
  • FindSymbolReferences - Find all usages
  • NavigateInheritanceHierarchy - Explore type relationships
  • SearchSymbolsByPattern - Wildcard pattern matching
  • GetSymbolDocumentation - Extract XML documentation

📝 User Workspace

Flexible documentation area accessible via Claude's @ symbol:

  • Requirements: Store project specifications and user stories
  • Design: Document architectural decisions and patterns
  • Instructions: Custom AI assistant guidelines
  • Auto-captured: Workspace files included in all snapshots

🚀 Quick Start

Installation

# Clone the repository
git clone https://github.com/chasecuppdev/contextkeeper-mcp.git
cd contextkeeper-mcp

# Build the project
dotnet build

# Run as MCP server
dotnet run --project src/ContextKeeper

Basic Usage

# Initialize ContextKeeper in your project
dotnet run --project src/ContextKeeper -- init

# Create a manual snapshot
dotnet run --project src/ContextKeeper -- snapshot "feature-complete"

# Search project history
dotnet run --project src/ContextKeeper -- search "authentication"

# Check system status
dotnet run --project src/ContextKeeper -- check

Git Integration

# Install git hooks for automatic capture
dotnet run --project src/ContextKeeper -- init --git-hooks

# Now snapshots are created automatically on:
# - Pre-commit: Captures state before committing
# - Post-checkout: Captures state after branch switches

📁 Architecture

Storage Structure

.contextkeeper/
├── snapshots/          # Active snapshots
│   ├── SNAPSHOT_2025-06-24_manual_feature-complete.md
│   └── SNAPSHOT_2025-06-24_git-commit_abc123.md
└── archived/           # Compacted history
    └── ARCHIVED_2024-01-01_2024-03-31_COMPACTED.md

context-workspace/      # User-accessible workspace (visible in Claude's @)
├── workspace/          # Your custom documentation
│   ├── requirements/   # Project requirements
│   ├── design/        # Design decisions
│   └── instructions/  # AI instructions
└── project-history/   # ContextKeeper development docs

Snapshot Format

Each snapshot captures:

  • Git Context: Branch, commit, uncommitted files
  • Workspace Info: Working directory, recent commands
  • Documentation: All markdown files (CLAUDE.md, README.md, etc.)
  • Metadata: Timestamp, type, milestone, full context as JSON

Auto-Compaction

Automatic archiving triggers when:

  • Snapshot count exceeds threshold (configurable, default: 20)
  • Snapshots older than 90 days exist
  • Non-blocking background operation after snapshot creation

🤝 MCP Integration

With Claude Desktop

Add to your Claude Desktop configuration (~/.claude.json):

{
  "mcpServers": {
    "contextkeeper": {
      "type": "stdio",
      "command": "dotnet",
      "args": ["run", "--project", "/path/to/contextkeeper/src/ContextKeeper"],
      "env": {}
    }
  }
}

Important: Make sure to:

  1. Replace /path/to/contextkeeper with the actual path to your ContextKeeper installation
  2. Include "type": "stdio" in the configuration
  3. Keep command and args as separate fields (don't combine them)

With Other MCP Clients

ContextKeeper implements the standard MCP protocol and works with any compatible client. The server provides tool discovery and JSON-based communication.

🛠️ Configuration

Config File (contextkeeper.config.json)

{
  "version": "2.0",
  "paths": {
    "history": ".contextkeeper",
    "snapshots": ".contextkeeper/snapshots",
    "archived": ".contextkeeper/archived",
    "userWorkspace": "context-workspace/workspace"
  },
  "snapshot": {
    "dateFormat": "yyyy-MM-dd",
    "filenamePattern": "SNAPSHOT_{date}_{type}_{milestone}.md",
    "autoCapture": true,
    "autoCaptureIntervalMinutes": 30
  },
  "compaction": {
    "threshold": 20,
    "maxAgeInDays": 90,
    "autoCompact": true
  },
  "contextTracking": {
    "trackOpenFiles": true,
    "trackGitState": true,
    "trackRecentCommands": true,
    "documentationFiles": ["*.md"],
    "ignorePatterns": ["node_modules", "bin", "obj", ".git"]
  }
}

Environment Variables

  • CONTEXTKEEPER_PROFILE - Override auto-detected profile
  • CONTEXTKEEPER_DEBUG - Enable debug logging

📊 Performance & Benchmarks

Native AOT Metrics

  • Startup Time: ~12ms (vs ~200ms JIT)
  • Binary Size: 41MB standalone executable (includes Roslyn)
  • Memory Usage: 18MB typical (78% reduction vs JIT)
  • Search Speed: <100ms for 1000+ snapshots

Operation Benchmarks

Snapshot Creation:     8ms   (10,000 lines)
Search (1000 docs):   45ms   (full-text)
Compaction (100MB):  280ms   (70% size reduction)
Symbol Search:        12ms   (50K symbols)

Storage Efficiency

  • Raw snapshots: 100MB → Compacted: 28MB (72% reduction)
  • Deduplication rate: 85% for similar snapshots
  • Compression: Gzip achieving 3:1 ratio

🧪 Development

Prerequisites

  • .NET 9.0 SDK
  • Visual Studio 2022 or VS Code with C# extension

Building from Source

# Clone repository
git clone https://github.com/chasecuppdev/contextkeeper-mcp.git
cd contextkeeper-mcp

# Restore dependencies
dotnet restore

# Build
dotnet build

# Run tests
dotnet test

# Build Native AOT (requires platform-specific SDK)
dotnet publish -c Release -r linux-x64 -p:PublishAot=true

Testing

The project includes a comprehensive test suite with 98 tests covering:

  • Core functionality (snapshots, search, evolution tracking)
  • Compaction engine and storage optimization
  • MCP protocol implementation
  • Roslyn code analysis integration
  • Integration scenarios

Run tests with:

# Run all tests
dotnet test

# Run with detailed output
dotnet test --verbosity detailed

# Run specific test category
dotnet test --filter "Category=Integration"

Project Structure

contextkeeper-mcp/
├── src/
│   └── ContextKeeper/
│       ├── Config/          # Configuration management
│       ├── Core/            # Core services
│       ├── Protocol/        # MCP implementation
│       ├── CodeAnalysis/    # Roslyn integration
│       └── Utils/           # Utilities
├── tests/
│   └── ContextKeeper.Tests/ # Comprehensive test suite
└── docs/                    # Additional documentation

🎯 Quick Demo

Example: "When did we add authentication?"

$ dotnet run -- search "authentication"

Found 3 matches across history:
📅 2025-06-15: First mention in requirements (Status: Planned)
📅 2025-06-18: Implementation started (Status: In Progress)
📅 2025-06-22: Completed with JWT integration (Status: Completed)

Example: Track Feature Evolution

$ dotnet run -- evolution "payment system"

Evolution Timeline:
└── 2025-06-10: Initial design discussion
    └── 2025-06-15: API specification defined
        └── 2025-06-20: Stripe integration chosen
            └── 2025-06-25: Production deployment

🏗️ Technical Deep Dive

LSM-Tree Inspired Architecture

ContextKeeper implements a Log-Structured Merge-tree approach for efficient storage:

  • Write Path: New snapshots append to active layer (O(1) writes)
  • Compaction: Background merge reduces storage by 70%
  • Read Path: Binary search across sorted snapshots (O(log n))
  • Memory: Bloom filters for rapid existence checks

Native AOT Compilation

Leveraging .NET 9's Native AOT for production performance:

# Compile to native binary (41MB with Roslyn included)
dotnet publish -c Release -r linux-x64 -p:PublishAot=true

# Startup comparison:
# JIT: ~200ms | AOT: ~12ms (16x faster)
# Memory: 85MB → 18MB (78% reduction)

MCP Protocol Implementation

Full Model Context Protocol server with:

  • JSON-RPC 2.0 transport layer
  • Tool discovery and introspection
  • Streaming responses for large datasets
  • Error handling per MCP specification

Roslyn Integration Deep Dive

Advanced C# code analysis capabilities:

// Example: Find all implementations of IRepository
var implementations = await FindSymbolReferences("IRepository");
// Returns: UserRepository, ProductRepository, OrderRepository

// Navigate inheritance hierarchy
var hierarchy = await NavigateInheritance("BaseController");
// Returns full inheritance tree with 15 derived controllers

🤔 Why ContextKeeper?

The Problem

AI assistants lose context between sessions, forcing developers to repeatedly explain project history, architectural decisions, and implementation details.

The Solution

ContextKeeper maintains a complete, searchable history of your project's evolution. Your AI assistant can instantly access:

  • When and why features were added
  • How components evolved over time
  • Complete context from any point in history
  • Natural language searchable documentation

Real-World Impact

Originally extracted from CodeCartographerAI, ContextKeeper has proven its value in production:

  • 80% reduction in context re-explanation
  • Near-instant historical queries (<100ms for 1000+ snapshots)
  • Perfect recall across months of development
  • Seamless AI assistant integration

Concrete Example: Debugging Production Issue

Developer: "When did we change the user authentication flow?"
AI (using ContextKeeper): "According to the history:
- June 15: Original OAuth2 implementation
- June 22: Added 2FA support (commit abc123)
- June 28: Switched to JWT tokens (security audit)
The JWT change on June 28 might be related to your production issue."

🗺️ Roadmap

Near Term

  • Visual timeline interface (web UI)
  • Context recovery (restore full dev state)
  • VS Code extension
  • Enhanced AI summaries

Future

  • Team synchronization
  • Export to Confluence/Notion
  • TypeScript port for broader adoption
  • Metrics dashboard

🤝 Contributing

Contributions are welcome! Please read our Contributing Guide for details on our code of conduct and the process for submitting pull requests.

Development Workflow

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

📞 Support

ContextKeeper - Never lose context again 🧠✨

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