Academic Torrents API

Name: Academic Torrents API
Brand: Academic Torrents API
Availability: InStock

★ Only Publicly Available OpenAPI DocumentStorageObject StorageapiKey10 EndpointsREST

For Agents

Programmatically register research dataset torrents on Academic Torrents and group them into named collections so agents can publish, retrieve, and curate distributed datasets without scraping the web UI.

Install Jentic One Beta

Connect the Academic Torrents API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Academic Torrents API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Academic Torrents API.

Retrieve metadata for a specific torrent by infoHash, including title, description, and tags

Modify an existing torrent entry's title, description, or category fields

GET STARTED

Start building with Academic Torrents API

Explore with Jentic

View OpenAPI Document

Jentic publishes the only available OpenAPI specification for Academic Torrents API, keeping it validated and agent-ready. Academic Torrents is a community-maintained distributed repository for sharing large research datasets over BitTorrent, and its v2 API exposes operations for creating, retrieving, and modifying torrent entries and managing named collections of torrents. Authentication uses session-style credentials passed as cookies (uid, pass) or query parameters, and the API is hosted at academictorrents.com/apiv2. It is intended for researchers, archive maintainers, and dataset publishers who want to programmatically register, group, and manage torrents.

Use Cases

Patterns agents use Academic Torrents API for, with concrete tasks.

★ Publishing Research Dataset Torrents

Researchers and archive maintainers register new BitTorrent entries on Academic Torrents directly from a publication or release pipeline. The API accepts the infoHash plus title, description, and tag metadata at POST /entry, allowing automated registration when a new dataset is seeded. This avoids the manual web upload step and keeps catalog entries consistent across multiple datasets released for the same paper.

Call POST /entry with the infoHash of a newly seeded ImageNet variant, a descriptive title, and tags so it appears in the Academic Torrents catalog

Curating Dataset Collections by Research Topic

Curators assemble named collections of related dataset torrents for a research domain such as natural language processing or genomics. POST /collection creates the collection, and POST /collection/{collectionName}/add and /remove manage membership over time. Curators use this to maintain reading-list-style bundles that researchers can subscribe to and download in one batch.

Create a collection named 'nlp-benchmarks-2026' and add three benchmark dataset torrents to it by infoHash

Maintaining Catalog Metadata for Existing Datasets

Dataset maintainers correct or expand metadata on entries that were registered earlier — for example, fixing a license tag or extending a description with citation information. POST /entry/{infoHash} updates fields on an existing entry without re-uploading the data, since the underlying torrent is unchanged. This keeps the public catalog accurate as documentation evolves.

Update the description on an existing Academic Torrents entry to add a DOI citation for the underlying paper

Agent-Driven Dataset Discovery and Registration

An AI research assistant working through Jentic uses the Academic Torrents API to register newly produced datasets and to look up entries referenced in literature. The agent searches Jentic for the right operation, loads the input schema, and submits an entry without the developer wiring up cookie-based authentication by hand. Credentials live in the Jentic vault and are scoped per execution.

Through Jentic, search 'register a research dataset torrent', load the POST /entry schema, and create the entry for a freshly seeded dataset

Key Endpoints

10 endpoints — jentic publishes the only available openapi specification for academic torrents api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/entry

GET

/entry/{infoHash}

Retrieve a torrent entry by infoHash

POST

/entry/{infoHash}

Modify an existing torrent entry

POST

/collection

Create a new collection

POST

/collection/{collectionName}/add

Add a torrent to a collection

POST

/collection/{collectionName}/remove

Remove a torrent from a collection

POST

/collection/{collectionName}/delete

Delete a collection

POST

/entry

GET

/entry/{infoHash}

Retrieve a torrent entry by infoHash

POST

/entry/{infoHash}

Modify an existing torrent entry

POST

/collection

Create a new collection

POST

/collection/{collectionName}/add

Add a torrent to a collection

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Academic Torrents uid and pass values are stored encrypted in the Jentic vault. Agents call the API through Jentic using a scoped execution token, so the raw cookie credentials never enter the agent's context window.

Intent-based discovery

Agents search Jentic by intent — for example, 'register a research dataset torrent' — and Jentic returns the matching POST /entry operation with its input schema, so the agent can call the right endpoint without reading the Academic Torrents docs.

Time to first call

Direct integration with Academic Torrents takes 1-2 days to wire up cookie-based auth, parameter handling, and error retries. Through Jentic: under 1 hour — search, load, execute.

FAQs

Specific to using Academic Torrents API through Jentic.

Why is there no official OpenAPI spec for Academic Torrents API?

Academic Torrents does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Academic Torrents API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the Academic Torrents API use?

The API uses session-style API key authentication, passed either as cookies (uid and pass) on each request or as a uid query parameter. Through Jentic, these credentials are stored encrypted in the vault and injected at execution time so the values never enter agent context.

Can I create and manage collections of torrents with the Academic Torrents API?

Yes. POST /collection creates a named collection, POST /collection/{collectionName}/add and /remove manage membership by infoHash, and POST /collection/{collectionName}/delete removes the collection itself. There is no requirement that all torrents in a collection be authored by the same uploader.

What are the rate limits for the Academic Torrents API?

The OpenAPI spec does not document explicit rate limits. Academic Torrents is community-run, so treat it as best-effort and back off on HTTP errors. For automated registration of many entries, throttle to a few requests per second and retry on 5xx responses.

How do I register a new dataset torrent through Jentic?

Run pip install jentic, then search for 'register a research dataset torrent'. Jentic returns the POST /entry operation, and you load its input schema, supply the infoHash and metadata, and execute. The whole flow is three async calls — search, load, execute — and avoids hand-coding cookie auth.

Is the Academic Torrents API free to use?

Yes. Academic Torrents is a community-maintained free repository for research data, and the API does not charge for entry registration or collection management. You only need a registered account to obtain the uid/pass credentials used for authentication.

Academic Torrents API

Connect the Academic Torrents API to your agent

Capabilities

Start building with Academic Torrents API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs