Lightning Network MCP Server
by AbdelStark
The Lightning Network MCP Server enables AI models to interact with the Lightning Network, allowing them to pay invoices. It is MCP-compliant and facilitates seamless integration with AI applications.
Last updated: N/A
What is Lightning Network MCP Server?
A Model Context Protocol (MCP) server that allows AI models to pay invoices on the Lightning Network. It acts as an intermediary, enabling AI to interact with the Lightning Network through a standardized protocol.
How to use Lightning Network MCP Server?
The server can be installed via Smithery or manually by cloning the repository, installing dependencies, and configuring the .env file with Lightning Network backend details (e.g., Lnbits). Once configured, the server can be started in development or production mode. The pay_invoice tool is available to pay Lightning invoices by sending a JSON payload with the invoice content.
Key features of Lightning Network MCP Server
Pay invoices on Lightning Network
MCP-compliant API for AI integration
Support for multiple Lightning Network backends (TODO)
stdin transport mode (TODO)
Use cases of Lightning Network MCP Server
AI agents paying for services
Automated micro-payments
Integrating Lightning payments into AI workflows
Contextual payments triggered by AI models
FAQ from Lightning Network MCP Server
What is MCP?
What is MCP?
MCP stands for Model Context Protocol, a standard for AI models to interact with external services.
What is Lnbits?
What is Lnbits?
Lnbits is a free and open-source Lightning Network wallet and accounts system.
How do I configure the server?
How do I configure the server?
You need to create a .env file and provide the necessary Lightning Network backend details, such as the Lnbits URL and API keys.
How do I pay an invoice?
How do I pay an invoice?
Use the pay_invoice tool by sending a JSON payload containing the Lightning invoice.
Can I contribute to the project?
Can I contribute to the project?
Yes, you can fork the repository, create a feature branch, commit your changes, and open a pull request.