What is Claude Agent Mcp

claude-agent-mcp is an advanced AI agent platform that integrates Claude 3.7 and utilizes the Model Context Protocol (MCP) for cross-platform capabilities, enabling multi-agent coordination and blockchain connectivity.

Use cases

Use cases for claude-agent-mcp include automated customer service agents, collaborative research assistants, blockchain transaction facilitators, and personal AI assistants that manage and coordinate tasks across different platforms.

How to use

To use claude-agent-mcp, users can interact with the platform through various interfaces such as CLI, Terminal Dashboard, or Web Dashboard. Users can initiate queries and manage conversations, leveraging the multi-agent system for efficient responses.

Key features

Key features include an advanced multi-agent system, zero-knowledge integration for privacy, blockchain connectivity with Phantom wallet, full MCP support, AGI reasoning capabilities, enhanced memory systems, integrated web research, and conversation management.

Where to use

claude-agent-mcp can be used in various fields such as customer support, research, software development, and any domain requiring complex query handling and multi-agent collaboration.

OrganiX Agent

| Twitter @0xOrganix

OrganiX is an advanced AI agent platform with powerful cross-platform capabilities, featuring Claude 3.7 integration, MCP (Model Context Protocol), multi-agent coordination, and blockchain connectivity.

Key Features

• 🧠 Advanced Multi-Agent System: Specialized agents coordinate to handle different types of queries
• 🪄 Zero-Knowledge Integration: Privacy-preserving verification through ZK proofs
• 🔗 Blockchain & Phantom Wallet: Solana blockchain integration with Phantom wallet connectivity
• 🛠️ Full MCP Support: Integrate external tools using Composio’s Model Context Protocol
• 💡 AGI Reasoning Capabilities: Complex reasoning through multi-agent collaboration
• 🧩 Enhanced Memory: Multi-tiered memory system with importance ratings and caching
• 🔍 Web Research: Integrated search and information extraction
• 💬 Conversation Management: Save, load, and manage multiple conversation sessions
• 🖥️ Cross-Platform: Works seamlessly on Windows, Linux, and cloud environments
• 📱 Multiple Interfaces: CLI, Terminal Dashboard, and Web Dashboard options

System Architecture

graph TD
    User[User] --> UI[User Interface]
    UI --> Agent[Core Agent]
    
    Agent --> MultiAgent[Multi-Agent Coordinator]
    Agent --> Memory[Memory System]
    Agent --> MCP[MCP Manager]
    
    MultiAgent --> ResearchAgent[Research Agent]
    MultiAgent --> CodeAgent[Code Agent]
    MultiAgent --> BlockchainAgent[Blockchain Agent]
    MultiAgent --> MCPAgent[MCP Agent]
    MultiAgent --> AGIAgent[AGI Reasoning Agent]
    
    MCP --> ComposioAPI[Composio API]
    MCP --> ExternalTools[External Tools]
    
    Agent --> Claude[Claude 3.7 API]
    Agent --> Blockchain[Blockchain Integration]
    Blockchain --> Solana[Solana Network]
    Blockchain --> ZK[Zero-Knowledge Proofs]
    Blockchain --> Phantom[Phantom Wallet]
    
    Memory --> EpisodicMem[Episodic Memory]
    Memory --> SemanticMem[Semantic Memory]
    Memory --> ProceduralMem[Procedural Memory]
    
    subgraph "User Interfaces"
        CLI[CLI Interface]
        TUI[Terminal Dashboard]
        WebUI[Web Dashboard]
    end
    
    UI --> CLI
    UI --> TUI
    UI --> WebUI

Memory System

The enhanced memory system uses ChromaDB for vector storage and retrieval, with three distinct memory types:

graph LR
    A[User Query] --> B[Agent Processing]
    B --> C[Memory System]
    
    C --> D[Episodic Memory]
    C --> E[Semantic Memory]
    C --> F[Procedural Memory]
    
    D -->|Stores| G[Conversations]
    D -->|Tracks| H[User Interactions]
    
    E -->|Stores| I[Key Facts]
    E -->|Organizes| J[Research Results]
    
    F -->|Records| K[Tool Usage Patterns]
    F -->|Remembers| L[System Operations]
    
    C --> M[Memory Maintenance]
    M -->|Prunes| N[Old Memories]
    M -->|Preserves| O[Important Memories]
    
    C --> P[Memory Retrieval]
    P -->|Based on| Q[Relevance]
    P -->|Filtered by| R[Importance]
    P -->|Organized by| S[Timeframe]

Quick Start

Using the Launch Script (Recommended)

The easiest way to get started is by using the launcher:

1. Clone this repository

git clone https://github.com/kabrony/claude-agent-mcp.git
cd claude-agent-mcp

2. Run the launcher for your platform:

   • Windows: launch_agent.bat
   • Linux/Mac: ./launch_agent.sh

3. Follow the on-screen menu to initialize your environment and launch the agent

Manual Setup

1. Clone this repository
2. Install dependencies:
   • Windows: install_dependencies.bat
   • Linux/Mac: ./install_dependencies.sh
3. Create a .env file with your API keys (see Environment Variables section)
4. Activate the virtual environment:
   • Windows: venv\Scripts\activate
   • Linux/Mac: source venv/bin/activate
5. Run the agent: python agent.py

Environment Variables

Create a .env file in the project root with the following variables:

# Required
ANTHROPIC_API_KEY=your_anthropic_api_key_here
CLAUDE_MODEL=claude-3-7-sonnet-20250219

# Optional - Web Research
EXA_API_KEY=your_exa_api_key_here

# Optional - MCP Integration
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_CONNECTION_ID=your_composio_connection_id_here
COMPOSIO_INTEGRATION_ID=your_composio_integration_id_here

# Optional - Blockchain
SOLANA_RPC_URL=https://api.mainnet-beta.solana.com
SOLANA_PRIVATE_KEY=your_solana_private_key_here

# Optional - Zero-Knowledge Proofs
ENABLE_ZK_PROOFS=true

# Optional - Social Media
TWITTER_BEARER_TOKEN=your_twitter_bearer_token_here

User Interfaces

Terminal Dashboard

# Launch the dashboard
python dashboard.py

# Start dashboard with initial query
python dashboard.py --query "What's the latest news on AI?"

The enhanced dashboard provides:

• Real-time conversation history with markdown rendering
• System information monitoring
• Detailed memory statistics and analytics
• Tool availability indicators
• Multiple conversation management
• Model switching capabilities
• Interactive query input with extended thinking option

Command Line Interface

# Process a query
python agent.py --query "What is quantum computing?"

# Stream a response (real-time output)
python agent.py --query "Tell me about quantum computing" --stream

# Use tools for a query
python agent.py --query "List the files in my current directory" --tools

# Use extended thinking mode
python agent.py --query "Explain the theory of relativity" --extended-thinking

# Research a topic
python agent.py --research "Climate change solutions"

# Display agent information
python agent.py

# Perform memory maintenance
python agent.py --maintenance

# Save conversation to file
python agent.py --save my_conversation.json

# Load conversation from file
python agent.py --load my_conversation.json

Web Dashboard

# Start the web server
python web_server.py

Then open your browser to http://localhost:8080

Advanced Features

Multi-Agent System

OrganiX uses a multi-agent architecture with specialized agents:

# Use collaborative reasoning with multiple agents
result = await coordinator.collaborative_reasoning(
    "Compare traditional finance with DeFi on Solana",
    agents=["researcher", "blockchain", "agi_reasoner"]
)

Blockchain & Phantom Wallet Integration

# Get Solana account balance
balance = await solana_integration.get_solana_balance(address)

# Connect to Phantom wallet
connection_url = solana_integration.generate_phantom_connection_url(
    dapp_url="https://example.com",
    redirect_url="https://example.com/callback"
)

Zero-Knowledge Proofs

# Create a proof of knowledge
proof = await zk_proofs.create_proof_of_knowledge(sensitive_data)

# Verify a proof
verification = zk_proofs.verify_proof(proof)

MCP Tool Integration

# Register a custom tool
mcp_manager.register_tool(
    "calculate_mortgage",
    "Calculate mortgage payments",
    calculate_mortgage_function
)

# Process with MCP tools
result = await mcp_manager.process_with_tools(
    "What's my monthly payment on a $300,000 loan at 4.5% for 30 years?"
)

Documentation

For complete documentation, see DOCUMENTATION.md

Requirements

• Python 3.8 or higher
• Dependencies listed in requirements.txt

License

MIT License

Acknowledgments

• Built with Anthropic Claude 3.7
• Utilizes ChromaDB for vector storage
• Enhanced with Exa for web search capabilities
• Integrates with Composio for MCP
• Connects with Solana and Phantom
• Terminal UI powered by Rich