MLflow
MLflow MCP Server provides a natural language interface to MLflow tracking servers through the Model Context Protocol. It exposes core MLflow functionality as standardized tools that AI assistants can use to query and manage machine learning experiments and models. The server connects to a local MLflow instance and offers tools for listing registered models, exploring experiments, retrieving detailed model information, and checking system status - making it valuable for data scientists who want to interact with their MLflow environment using conversational AI rather than programming 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 2026-09-28.
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
- ai-ml
- Source
- PulseMCP
- Repository
- github.com/irahulpandey/mlflowmcpserver
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve MLflow 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.