ZenML
This ZenML MCP server enables AI assistants to interact with ZenML, an open-source ML pipeline management platform. Built with Python using FastMCP, it provides tools to access core ZenML functionality including users, stacks, pipelines, runs, services, components, artifacts, and logs. The implementation allows querying pipeline metadata, triggering new pipeline runs, and analyzing run history through standardized MCP tools. It handles authentication via API keys and includes robust error handling, making it ideal for ML engineers who want to monitor and manage their machine learning workflows through conversational AI interfaces.
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 2026-09-01.
Scan details: Circle-IR · 2026-09-01 · 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/zenml-io/mcp-zenml
- Author type
- human
- Last scanned
- 2026-09-01
- Updated
- 2026-09-01
Use via MCP
Resolve ZenML 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.