> For the complete documentation index, see [llms.txt](https://icij.gitbook.io/datashare/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://icij.gitbook.io/datashare/server-mode/add-documents-from-the-cli.md).

# Add documents from the CLI

The shortest path from an empty project to searchable documents on a server install.

**This document assumes that you have installed Datashare** [**in server mode within Docker**](/datashare/server-mode/install-with-docker.md)**.**

In server [mode](/datashare/concepts/running-modes.md), Datashare has no web interface to add documents. Documents are added from the command line.

Here is the shortest command that scans a directory and indexes its files:

```bash
docker compose exec datashare /entrypoint.sh \
  stage run \
  --stages SCAN,INDEX \
  --defaultProject secret-project \
  --elasticsearchAddress http://elasticsearch:9200 \
  --dataDir /home/datashare/Datashare/
```

What is happening:

* Datashare runs the SCAN and INDEX [stages](/datashare/concepts/cli-stages.md) together, SCAN filling a queue with the files it finds and INDEX draining it.
* Files are read from `/home/datashare/Datashare/`, which is a directory mounted from the host machine, so this is the path **inside the container**.
* Extracted documents are written to the `secret-project` index in Elasticsearch.

Once the command exits, your documents are searchable.

{% hint style="warning" %}
That command is fine for a first try on a small directory. For a real corpus, add at least `--reportName` (so the run can resume) and `--queueType REDIS` (so the queue survives the process), and decide whether you want OCR. All of that is covered in [Indexing](/datashare/server-mode/indexing.md).
{% endhint %}

## Next steps

* [Indexing](/datashare/server-mode/indexing.md): the full guide to indexing on a server.
  * [Scenarios](/datashare/server-mode/indexing/scenarios.md): incremental updates, resuming, distributing across machines, mail archives.
  * [Options](/datashare/server-mode/indexing/options.md): every command-line flag, environment variable and settings key.
  * [Tuning](/datashare/server-mode/indexing/tuning.md): parallelism, OCR, memory and Elasticsearch.
  * [Troubleshooting](/datashare/server-mode/indexing/troubleshooting.md): what the errors mean.
* [Add entities from the CLI](/datashare/server-mode/add-entities-from-the-cli.md): extract people, organizations and locations from documents you have indexed.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://icij.gitbook.io/datashare/server-mode/add-documents-from-the-cli.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
