Lightning AI is an open-source framework for deep learning research and model development. It simplifies the process of building, training, and deploying machine learning models while maintaining full control and flexibility for researchers and developers.
Provides tools for managing an RGB Lightning Node (RLN) wallet, including on-chain and Lightning balances, RGB asset management, Lightning invoices and payments, channel operations, and atomic swap taker support.
Exposes an RGB Lightning Node wallet to AI agents, enabling full wallet control including balances, RGB invoices, Lightning payments, channel management, and atomic swap taker support.
19
Apache 2.0
Why this server?
Provides tools for Lightning Network operations including invoice creation and payment, Lightning address payments, and LNURL support.
Enables AI assistants to interact with the Blink Bitcoin and Lightning Network API for managing wallets, payments, invoices, and L402 services.
55
14 npm
1
MIT
Why this server?
Enables AI agents to answer questions about Cryptbrew's Bitcoin Lightning payment handling, including auto-forwarding of invoices to a merchant's Lightning wallet, the 1% / 10 sats minimum fee, and Breez Lock-adjacent details.
Enables AI agents to answer Cryptbrew product questions and check live API health without merchant authentication. Exposes tools for pricing, FAQs, invoice flow, and health probes over stdio or streamable HTTP.
8
MIT
Why this server?
Allows interaction with the Lightning Network's L402 protocol for agent payments and service discovery.
Connects AI agents to Bitcoin payment rails with owner-defined spending policies and limits.
26
19 npm
MIT
Why this server?
Provides Lightning Network operations including creating and paying invoices, managing channels, and handling RGB asset transfers over the Lightning Network.
Enables AI assistants to interact with RGB assets, Lightning Network operations, and Bitcoin transactions through RGB Lightning Node APIs. Supports asset management, invoice creation/payment, channel management, on-chain transactions, and asset swaps.
18
6 npm
1
MIT
Why this server?
Imports PyTorch Lightning `lightning_logs/version_*` runs, capturing hparams and the last values from each run's `metrics.csv` so prior training runs appear in the experiment tree.
Turns an ML/QSAR/GNN workflow into a DAG of pipeline steps and its experiments into a branching run tree stored as plain files in the repository. Lets coding assistants register steps, log runs with params, metrics and artifacts, scan existing projects statically, and open a KNIME-style browser view of the map.
21
MIT
Why this server?
Runs training jobs on free Lightning AI T4 GPUs, spending Lightning credits, enforcing gpu-router's 4h per-job cap, and rerouting to another provider when credits or a session run out.
Enables AI agents and their users to submit, route, and monitor training jobs across free-tier GPU clouds (Kaggle, Colab, Lightning, local MPS) through a local daemon that tracks quota, explains routing decisions, and gates long or secret-reading agent jobs behind human approval.
8
1
MIT
Why this server?
Provides tools for Bitcoin Lightning Network operations, enabling payment processing and wallet management through the Nostr Wallet Connect protocol.
