Implements Git-like versioning for sessions with content-addressable storage, branching and restoration capabilities
Enables GitHub import capabilities for code repositories and integration with Claude Code workflows
Supports discovery of Claude Code binaries installed via NVM as part of the multi-method search approach
Implements observability features using OpenTelemetry for monitoring and tracing Claude Code operations
Leverages SQLite with aiosqlite for optimized database storage and content-addressable storage functionality
Shannon MCP - Claude Code MCP Server
A comprehensive Model Context Protocol (MCP) server implementation for Claude Code, built using an innovative multi-agent collaborative system.
Overview
Shannon MCP is a Python-based MCP server that provides programmatic management of Claude Code CLI operations. This project replicates and extends the functionality found in the Claude Desktop application, exposing all Claude Code interactions through standardized MCP tools.
Multi-Agent Architecture
This project employs a revolutionary approach: 26 specialized AI agents working collaboratively to implement the entire MCP server specification. Each agent has deep expertise in specific domains and works together through shared memory and orchestration systems.
System Architecture
Agent Categories
1. Core Architecture Agents (4)
Architecture Agent: System design and architectural decisions
Claude Code SDK Expert: Deep knowledge of Claude Code CLI and SDK
Python MCP Server Expert: MCP protocol implementation specialist
Functional MCP Server: Business logic and feature implementation
2. Infrastructure Agents (7)
Database Storage: SQLite optimization and content-addressable storage
Streaming Concurrency: Async patterns and stream processing
JSONL Streaming: Real-time JSONL parsing and handling
Process Management: System process monitoring
Filesystem Monitor: Real-time file system change detection
Platform Compatibility: Cross-platform support
Storage Algorithms: Content-addressable storage optimization
3. Quality & Security Agents (6)
Security Validation: Input validation and security implementation
Testing Quality: Comprehensive test implementation
Error Handling: Error recovery and user-friendly messages
Performance Optimizer: Performance profiling and optimization
Documentation: Technical documentation and examples
DevOps Deployment: CI/CD and deployment automation
4. Specialized Agents (9)
Telemetry OpenTelemetry: Observability implementation
Analytics Monitoring: Usage analytics and reporting
Integration Specialist: Third-party integrations
Project Coordinator: Overall project management
Migration Specialist: Database and config migrations
SSE Transport: Server-Sent Events implementation
Resources Specialist: MCP resource exposure
Prompts Engineer: MCP prompt templates
Plugin Architect: Plugin system design
How It Works
1. Orchestration Layer
The orchestration layer coordinates all agent activities through specialized commands:
/mcp-build-orchestrator
: Master command that distributes tasks to agents/mcp-agent-progress
: Tracks real-time progress of all agents/mcp-shared-memory
: Enables knowledge sharing between agents/mcp-agent-context
: Manages persistent context for each agent
2. Agent Collaboration
Agents collaborate through several mechanisms:
3. Implementation Workflow
Building Process
The building process follows these phases:
Phase 1: Core Infrastructure (25 tasks)
Project setup and MCP server foundation
Binary Manager implementation
Session Manager with streaming
Basic error handling
Phase 2: Advanced Features (25 tasks)
Agent system implementation
MCP server management
Checkpoint system with CAS
Hooks framework
Phase 3: Analytics & Monitoring (15 tasks)
Analytics engine
Process registry
Settings management
Phase 4: Testing & Documentation (10 tasks)
Integration testing
API documentation
Usage examples
Phase 5: Production Readiness (10 tasks)
Performance optimization
Security hardening
Deployment pipeline
Phase 6: Advanced Integration (10 tasks)
Claude Desktop integration
Cloud features
Enterprise capabilities
Key Features
1. Binary Management
Automatic Claude Code discovery
Version detection and validation
Multi-method search (PATH, NVM, standard locations)
2. Session Orchestration
Real-time JSONL streaming
Full process lifecycle management
Cancellation and cleanup
3. Agent System
Custom AI agents with specialized prompts
Background execution tracking
GitHub import capabilities
4. Checkpoint System
Git-like versioning for sessions
Content-addressable storage
Branching and restoration
5. Hooks Framework
Event-driven automation
Command execution on Claude events
Flexible configuration
Getting Started
Prerequisites
Python 3.11+
Claude Code CLI installed
100MB disk space
Agent System Activation
# The agents are already installed in ~/.claude/ # Activate the system python ~/.claude/activate-mcp-system.pyInitialize Build Process
# Use the orchestrator to start building /mcp-build-orchestrator init --project-path ~/shannon-mcpMonitor Progress
# Check agent progress /mcp-agent-progress status --detailed
Technical Stack
Language: Python 3.11+
Async Framework: asyncio
MCP SDK: FastMCP pattern
Storage: SQLite with aiosqlite
Compression: Zstandard
Streaming: JSONL with backpressure handling
Development Workflow
Agents analyze the specification
Tasks are distributed based on expertise
Implementation happens in parallel
Cross-agent reviews ensure quality
Integration testing validates components
Documentation is generated automatically
Contributing
This project is built by AI agents, but human contributions are welcome for:
Bug reports and feature requests
Testing and validation
Documentation improvements
Integration examples
License
MIT License - See LICENSE file for details
Acknowledgments
Built using Claude Code's multi-agent capabilities
Based on the Model Context Protocol specification
Inspired by collaborative AI development patterns
This project demonstrates the future of software development: specialized AI agents working together to build complex systems with minimal human intervention.
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
A comprehensive Model Context Protocol server for Claude Code that provides programmatic management of Claude Code CLI operations through a multi-agent collaborative system.
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