Equip your AI to dynamically search, run, and monitor thousands of open-source machine learning models hosted on Replicate via simple text commands.

Connect your AI to Supabase Vector. Execute pgvector semantic searches, manage embeddings, and run relational database queries directly from your terminal.

Generate code, evaluate embeddings, and deploy open-source LLMs instantly from your local agent via Together AI's infrastructure.

Track experiments, monitor ML runs, and manage artifacts on WandB — the developer platform for AI.

Manage AI inference via Clarifai — list apps, models, and workflows, and perform computer vision predictions directly from any AI agent.

Manage AI infrastructure via Lambda Labs — launch GPU instances, monitor ML workloads, and manage SSH keys.

Manage AI-powered search via Lucidworks Fusion — execute semantic queries, index documents, and monitor ML training jobs.

Manage ML experiments via DVC — track projects and views, audit experiments history, and monitor model runs directly from any AI agent.

Manage AI models via H2O.ai — track data frames, monitor machine learning models and training jobs, and audit cloud cluster status directly from any AI agent.

Manage AI-powered data via MindsDB — execute SQL predictions, audit ML models, and connect data sources.

Analyze and extract data from text via MonkeyLearn — sentiment analysis and keyword extraction directly from your AI agent.

Provision and track powerful GPU workloads via Paperspace — list compute instances, fetch active deployments, trace team projects, and query Gradient environments via AI.

Manage machine learning-powered advertising via Moloco — track campaigns and get analytics directly from your AI agent.

Classify data and perform semantic search via Nyckel — track ML functions, samples, and labels directly from your AI agent.

AI document extraction orchestration — parse PDFs, images, and Word docs via AI.

No-code NLP and AI model management via Metatext — run inference and manage datasets.

Power your agent with Vald — query, insert, and manage dense vectors on a highly scalable, distributed nearest-neighbor engine.