Maestro MCP Server Integration

What does “Maestro” MCP Server do?

Maestro MCP Server is designed to connect AI assistants with the Bitcoin ecosystem, enabling them to interact with Bitcoin-related data and functions in a secure and programmable manner. By exposing standardized endpoints and tools via the Model Context Protocol (MCP), the Maestro MCP Server allows developers to automate tasks like blockchain queries, transaction management, and potentially other Bitcoin network operations. This integration streamlines workflows for developers building Bitcoin applications or AI agents that require access to real-time, trustworthy blockchain data, and operational capabilities. It is especially useful for automating repetitive blockchain tasks, enhancing productivity, and ensuring reliable, consistent access to Bitcoin infrastructure for AI-driven development scenarios.

List of Prompts

No information about prompt templates is available in the repository.

List of Resources

No explicit resources documented in the repository.

List of Tools

No detailed tool listings found in server.py or similar entry point files.

Use Cases of this MCP Server

• Bitcoin Transaction Monitoring: Automate the tracking of Bitcoin transactions for wallets or addresses, enabling real-time alerts and data extraction for developers.
• Blockchain Data Queries: Allow AI assistants or applications to fetch up-to-date information about blocks, addresses, balances, and other on-chain data.
• Automated Bitcoin Payments: Enable programmatic initiation and management of Bitcoin payments or transfers through AI workflows.
• Wallet Management: Facilitate development of tools or assistants that can create, manage, and interact with Bitcoin wallets securely.
• Compliance and Auditing: Streamline the process of extracting audit trails and transaction histories for compliance or reporting purposes.

How to set it up

Windsurf

1. Ensure Node.js is installed on your system.
2. Navigate to your Windsurf project configuration directory.
3. Add Maestro MCP Server to your mcpServers configuration as shown below.
4. Save your configuration and restart Windsurf.
5. Verify that Maestro MCP Server is available in your tools list.

Example JSON:

{
  "mcpServers": {
    "maestro": {
      "command": "npx",
      "args": ["@maestro/mcp-server@latest"]
    }
  }
}

Claude

1. Install Node.js if not already available.
2. Locate the Claude configuration file for MCP integrations.
3. Insert the Maestro MCP Server definition as below.
4. Save changes and restart Claude.
5. Confirm the server is operational.

Example JSON:

{
  "mcpServers": {
    "maestro": {
      "command": "npx",
      "args": ["@maestro/mcp-server@latest"]
    }
  }
}

Cursor

1. Make sure Node.js is installed.
2. Open Cursor’s configuration for MCP servers.
3. Add Maestro MCP Server using the JSON snippet below.
4. Restart Cursor to apply changes.
5. Check tool availability.

Example JSON:

{
  "mcpServers": {
    "maestro": {
      "command": "npx",
      "args": ["@maestro/mcp-server@latest"]
    }
  }
}

Cline

1. Verify Node.js is set up on your system.
2. Edit the Cline configuration to add an MCP server.
3. Insert the Maestro MCP Server JSON configuration.
4. Save and restart the Cline environment.
5. Ensure Maestro MCP features are accessible.

Example JSON:

{
  "mcpServers": {
    "maestro": {
      "command": "npx",
      "args": ["@maestro/mcp-server@latest"]
    }
  }
}

Securing API Keys

To secure sensitive keys, use environment variables and pass inputs accordingly:

{
  "mcpServers": {
    "maestro": {
      "command": "npx",
      "args": ["@maestro/mcp-server@latest"],
      "env": {
        "MAESTRO_API_KEY": "${MAESTRO_API_KEY}"
      },
      "inputs": {
        "apiKey": "${MAESTRO_API_KEY}"
      }
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "maestro": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “maestro” to whatever the actual name of your MCP server is (e.g., “github-mcp”, “weather-api”, etc.) and replace the URL with your own MCP server URL.

Overview

Based on the above, Maestro MCP Server presents a basic integration for Bitcoin-related actions but lacks detailed documentation on prompts, resources, and tool specifics. Setup examples are generic, and security is considered. For now, the server scores low on comprehensive MCP-specific features.

Our opinion

Given the current lack of explicit prompts, resource, and tool documentation, Maestro MCP Server seems to be in an early or minimal documentation phase. Its value is high for Bitcoin workflows, but its MCP integration features (like Roots and Sampling) are not described. I’d rate this MCP server a 3/10 based on documentation, usability, and MCP compliance.

MCP Score