MCP Tools

Tools exposed by the Studio MCP server. The last column is the token scope and role a tool needs; OAuth sessions get both scopes.

Tool	What it does	Access
`search_knowledge_base`	Full-text search over the generated knowledge of datasets and storages	Datasets: read
`list_datasets`	List datasets that have a complete version, filtered by namespace and project	Datasets: read
`get_dataset`	Return a dataset's schema, versions, knowledge page, and up to 5 preview rows	Datasets: read
`get_row_content`	Read the file a dataset row points to, as an image or text	Datasets: read
`list_storages`	List indexed storage roots	Datasets: read
`get_storage`	Return an indexed storage's listing statistics and knowledge page	Datasets: read
`get_knowledge_base`	Return a Markdown index of enriched datasets and storages	Datasets: read
`enrich_dataset`	Generate the knowledge page for one dataset, using the team's provider and budget	Datasets: write
`enrich_all`	Generate pages for every dataset and storage that lacks a current one	Datasets: admin
`get_datachain_guide`	Return the DataChain SDK rules a `run_job` script must follow	Jobs: read
`list_clusters`	List the team's compute clusters, default first	Jobs: read
`run_job`	Submit a Python DataChain script as a Studio job	Jobs: write
`get_job`	Return a job's settings, status, progress, errors, and produced dataset versions	Jobs: read
`get_job_logs`	Return a job's most recent log lines	Jobs: read
`cancel_job`	Cancel an active job	Jobs: write

get_dataset previews at most 5 rows and truncates each cell to 200 characters.
get_row_content reads files from s3://, gs://, az://, and hf:// only, up to 4 MiB; JPG, PNG, GIF, and WebP come back as images, UTF-8 files as text.
search_knowledge_base returns at most 50 matches per call; list_datasets at most 200 datasets per page.
Requests are rate limited per user and per IP address; a limited request gets HTTP
Wait and retry.
Knowledge search and the knowledge index cover only datasets and storages with a generated page; enrich_dataset and enrich_all generate pages using the team's provider and budget.

What datasets do we have about product images? Show the schema of the largest one.

Find storages with audio files and summarize what the knowledge base says about them.

The loop that makes an agent and Studio worth combining: a question comes in, no existing column answers it, the agent runs a pass over the files, saves the result as a dataset, and the next person who asks gets it from the store.

Do we already have embeddings for the oxford-pets images?

Which pets in s3://dc-readme/oxford-pets-micro/ were photographed outdoors?

Why did job <job-id> fail? Show the relevant log lines.

Limits

Example prompts