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Manage Hopsworks platforms, feature stores, models, and jobs through LLM workflows.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Hopsworks MCP Server" yet — see the docs or source repo.
Connect to Hopsworks, list the feature groups in the current project, and summarize each group’s primary keys, feature count, and last update time.
A list of feature groups with key metadata summaries for quickly understanding the feature store structure.
In Hopsworks, find the most recently registered model versions and summarize their version numbers, status, linked datasets, and latest deployment records.
An overview of model versions and lifecycle states to help decide what to deploy or roll back.
Read the latest 10 job run records in Hopsworks, report success rate, average duration, failure reasons, and flag issues that need immediate attention.
A job run analysis highlighting failed or abnormal tasks and actionable investigation priorities.
Configure and manage Higress through MCP with agent-driven operations.
Give LLMs safe structured access to reverse-engineering snapshots for binary analysis.
Manage MCP server configurations with listing, toggling, and version control.
Give AI agents unified access to Harness for deployment and DevOps workflows.
Use MCP tools to manage GitHub repos, search code, and handle issues and pull requests.
Connect small business data systems for documents, queries, and report generation.