ML Lab
ML Lab provides a comprehensive machine learning training and experimentation platform that bridges multiple cloud providers, training backends, and inference systems through a unified interface. The implementation supports fine-tuning workflows across OpenAI, Mistral, Together AI, and Vertex AI APIs, as well as local training with transformers/PEFT, while managing credentials securely through an encrypted vault system. It integrates cloud compute providers like Lambda Labs, RunPod, and Modal for scalable training, includes dataset management and experiment tracking, and connects to inference platforms like Ollama and OpenWebUI for model deployment.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- devops-ci
- Source
- PulseMCP
- Repository
- github.com/pushpullcommitpush/ml-mcp
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve ML Lab from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.