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Submit, monitor, and retrieve outputs for Neo AI/ML engineering tasks.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "Neo — AI/ML Engineering" MCP server from askskill: Run: claude mcp add 'io-github-neoairesearch-neo-mcp' -- uvx neo-mcp
Submit an image classification training job through Neo using dataset path /datasets/cats-dogs, train for 20 epochs, and return the job ID, estimated runtime, and output location.
Created training job details, including job ID, status, estimated runtime, and result storage path.
Check the current status of Neo job ID ml-job-4821, and show progress, recent logs, and whether there are any failures or retries.
A status summary with current progress, key log excerpts, and any failure or retry details.
Retrieve the outputs from the most recent text classification inference job in Neo, and list the generated files, download links, and the purpose of each file.
A list of inference artifacts with filenames, access links, and descriptions for downstream analysis or delivery.
Enable AI agents to derive semantic addresses, search concepts, and manage personae.
Use natural language to generate images and manage SD Forge NEO models.
Manage Kaneo tasks, projects, labels, and comments through your AI assistant.
Query Neo4j graph databases with natural language for fast relationship insights.
Create and manage persistent AI agents with memory and tool access.
Query the latest NeoForge modding docs to answer API and development questions.