Lets an assistant search the Mozilla Data Collective catalog of AI training datasets and view their license, format and pricing details.
What you can do
It offers three tools. search queries the Mozilla Data Collective catalog of AI training datasets in natural language, optionally filtered by task, language, license, format, price, sample availability or publish date. fetch returns the full public details of one dataset by id or slug, including description, organization, task, locale, license, format, size, pricing and page URL. list_filters lists the accepted filter values plus sort and date-range options.
When to use it
Use it when you need to find AI training datasets with clear licensing and want to narrow results by task, language, license or format. It suits quick comparison of license, format, size and price before choosing a dataset.
Requirements
Network access to the remote endpoint. No local package, account, API key or environment variable is needed.
Before you install
The tools only read public catalog information; they do not download datasets or make purchases. Obtaining a dataset still means visiting its page and checking the license terms and pricing yourself.
Enable the server for the chats that should use its tools.
Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.
Use with an agent
Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.
Read https://sourceweft.com/mcp/com.mozilladatacollective%2Fdatasets/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.
Search the Mozilla Data Collective catalog of AI training datasets by natural-language query, optionally narrowed by task, language, license, format, price, sample availability or publish date. Returns matching datasets as {id, title, url}; pass an id to the fetch tool for full details. Call list_filters first if you intend to filter — filter values must match the catalog exactly.
Fetch the full public details of one Mozilla Data Collective dataset by id or slug: description, organization, task, locale, license, format, size, pricing, and its page URL.
Parametersidrequired
list_filters
List dataset filter values
List every value the search tool's filters accept: the tasks, locales, licenses and formats present in the catalog, plus the sort and date-range options. Task and license values are abbreviations, so taskLabels and licenseLabels spell them out. Filter values are matched exactly, so call this before filtering a search rather than guessing values. Takes no arguments.
Takes no parameters.
Version history
1
v0.1.0LatestSep 16, 2026
Score
72%
72% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
Reached in the last 30 daysRequired25 pts
Auth declaredRequired10 pts
Tools listedRequired15 pts
DescriptionRequired15 pts
Logo10 pts
Publish an icon in the registry entry.
Documentation15 pts
Declare a GitHub repository with a README, or serve resource_documentation in the OAuth protected-resource metadata.
LicenseNot applicable
A hosted service is used under its provider's terms, so no license is expected here. This check is left out of the percentage.