Python MCP server for XRP Ledger queries and AI tool integration
xrpx-mcp is a Python-based MCP (Model Context Protocol) server designed to facilitate real-time data integration between AI applications and the XRP Ledger, one of the world’s premier public blockchain networks. By leveraging MCP's universal adapter capabilities, this server enables developers to seamlessly connect various AI tools with XRP Ledger data, including account balances, ledger indices, and transaction histories.
xrpx-mcp provides essential functionalities to support an array of use cases in the AI domain:
Querying XRP Account Information: Users can easily retrieve critical information about any XRP account, such as balance details, sequence numbers, and ledger indices.
Integration with MCP-Capable AI Tools: xrp-mcp is compatible with a broad range of MCP clients, including Claude Desktop, Continue, Cursor, and others. This compatibility ensures that these advanced applications can interact efficiently with the XRP Ledger.
The protocol used by the server adheres to the Model Context Protocol (MCP) standards, which act as a bridge between AI applications and backend data sources or tools. By following MCP’s guidelines for communication, xrpx-mcp ensures efficient and standardized interaction between the AI application and the XRP Ledger infrastructure.
The architecture of xrpp-xmc is built on principles that ensure scalability, security, and performance:
Data Flow: The protocol flow diagram illustrates how data flows from an AI application through MCP clients to the xrp-mcp server and finally to the XRP Ledger. This structured communication pathway ensures that all parties have a clear understanding of data requirements.
graph TD
A[AI Application] -->|MCP Client| B[MCP Protocol]
B --> C[xrpx-mcp Server]
C --> D[XRP Ledger Data Source/Tool]
style A fill:#e1f5fe
style C fill:#f3e5f5
style D fill:#e8f5e8
Protocol Details: xrp-mcp follows MCP's protocol, providing methods for initiating connections, requesting data, and handling responses. This includes defining message formats, response codes, and error handling mechanisms to ensure seamless communication.
To get started with xrpx-mcp, follow these steps:
Clone the Repository:
git clone https://github.com/your-repo-url/xrpl-mcp.git
Install Dependencies: Use pip
to install all necessary packages specified in requirements.txt
.
pip install -r requirements.txt
Run the MCP Server:
python -m mcp_server_xrpl.server
xrpx-mcp enhances several key use cases in AI workflows by enabling real-time data integration with the XRP Ledger:
Real-Time Balance Monitoring: Financial AI applications can monitor and update account balances in real-time, ensuring accuracy and reducing latency.
Transaction Verification: AI tools like auditing software can verify transactions on the ledger to ensure integrity and compliance.
These use cases are implemented by querying specific endpoints provided by the xrp-mcp server. For example:
response = requests.get('http://localhost:5000/account_info?address=XX1234')
balance_data = response.json()
xrpx-mcp supports a variety of MCP clients, including:
Claude Desktop: Fully integrated and compatible with all xrp-mcp features.
Continue: Supports most functionalities but may require minor configuration adjustments.
Cursor: Limited support for specific queries due to compatibility constraints.
The following matrix provides an overview of the different levels of support across various MCP clients:
MCP Client | Resources | Tools | Prompts | Status |
---|---|---|---|---|
Claude Desktop | ✅ | ✅ | ✅ | Full Support |
Continue | ✅ | ✅ | ✅ | Full Support |
Cursor | ❌ | ✅ | ❌ | Tools Only |
This compatibility matrix helps developers determine the best AI tools to use with xrp-mcp based on their specific requirements.
xrpx-mcp is designed for high performance and broad compatibility. It supports various data retrieval methods, ensuring optimal response times and reliability. The server can handle a wide range of queries from both simple account information requests to complex transaction history checks.
The compatibility matrix not only outlines the supported features but also provides insights into potential limitations when using certain clients:
Feature | Status |
---|---|
Account Information Retrieval | ✅ |
Transaction History | ⬇️ |
Prompts & Chat Requests | ⚠️ |
This helps users understand which aspects of the server will work seamlessly and which may require additional configuration.
To ensure optimal performance and security, developers can configure xrp-mcp using a JSON file:
{
"mcpServers": {
"[server-name]": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-[name]"],
"env": {
"API_KEY": "your-api-key"
}
}
},
"security": {
"auth_enabled": true,
"api_key_required": true
}
}
Advanced configurations like enabling authentication and specifying required API keys enhance security by restricting unauthorized access.
Q: Are there any limitations to the MCP clients supported?
Q: What kind of performance issues might I encounter with transaction history requests?
Q: How do I configure security settings for the server?
auth_enabled
and api_key_required
in the JSON configuration file to ensure secure access.Q: Can any AI workflow use xrp-mcp effectively?
Q: How often should I update my API key for security reasons?
To contribute to xrp-mcp, follow these steps:
Fork the Repository: Go to the repository's homepage and fork it.
Create a Pull Request: Add your changes and submit a pull request for review.
Linting Checks: Ensure all code adheres to linting standards before submitting.
Testing: Run tests to confirm that everything functions as expected.
For further learning and support, explore the following resources:
MCP Specification: Detailed protocol documentation.
Community Forum: A space for developers to discuss ideas and solve issues.
By leveraging xrpx-mcp, developers can unlock new possibilities in AI integration with the XRP Ledger, driving innovation across multiple domains.
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