> ## Documentation Index
> Fetch the complete documentation index at: https://docs.infino.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# CLI

> The infino command-line interface — create tables, ingest data, and run BM25, vector, and SQL search from your terminal or a coding agent.

`infino` is the command-line interface to the retrieval engine: SQL, full-text
(BM25), and vector search over a single copy of your data on object storage, run
straight from your terminal — or driven by a coding agent. It wraps the same
engine as the [Python, Node, and Rust SDKs](/quickstart); there's nothing extra
to run.

## Install

<CodeGroup>
  ```bash Homebrew theme={null}
  brew install infino-ai/tap/infino-cli
  ```

  ```bash npm theme={null}
  npm install -g @infino-ai/infino-cli   # or run once with: npx @infino-ai/infino-cli
  ```

  ```bash cargo theme={null}
  cargo install infino-cli
  ```

  ```bash shell theme={null}
  curl --proto '=https' --tlsv1.2 -LsSf \
    https://github.com/infino-ai/infino-cli/releases/latest/download/infino-cli-installer.sh | sh
  ```
</CodeGroup>

All install the `infino` binary.

## Connect

Every command targets a storage location with `--uri` (or the `INFINO_URI`
environment variable):

| `--uri`                     | Storage                      |
| --------------------------- | ---------------------------- |
| `memory://`                 | in-process, ephemeral        |
| `file://<path>`             | local disk                   |
| `s3://<bucket>/<prefix>`    | Amazon S3 (or S3-compatible) |
| `az://<container>/<prefix>` | Azure Blob                   |

S3/Azure credentials are read from the ambient environment (`AWS_*`, `AZURE_*`).

## Quickstart

```bash theme={null}
# Create a table and load its first rows (body full-text indexed)
infino create-table docs --uri file://./data --schema schema.yaml --fts body --file seed.ndjson

# Append more rows
infino ingest docs --uri file://./data --file more.ndjson --format ndjson

# Search
infino bm25-search docs body "object storage" -k 10 --uri file://./data
infino query "SELECT id, body FROM docs LIMIT 10" --uri file://./data --output json
```

A table becomes durable on its first commit, so `create-table` loads initial
rows too — from a Parquet file (`--from-parquet`, which also infers the schema)
or a YAML schema plus `--file`.

## Commands

| Command                       | Description                                                                |
| ----------------------------- | -------------------------------------------------------------------------- |
| `create-table`                | Create a table and load initial rows; declare `--fts` / `--vector` indexes |
| `ingest`                      | Append rows from Parquet or NDJSON (file or stdin)                         |
| `bm25-search`                 | Ranked keyword (BM25) search                                               |
| `vector-search`               | Vector similarity (kNN) search                                             |
| `token-match` / `exact-match` | Unranked token / exact-value match                                         |
| `query`                       | Run SQL, including the `bm25_search()` / `vector_search()` table functions |
| `tables` / `describe`         | List tables / show a table's schema                                        |
| `update` / `delete`           | Change rows matching a `--where` SQL predicate                             |
| `optimize`                    | Compact a table                                                            |
| `skills install`              | Install the bundled agent skills for Claude Code / Cursor                  |

Run `infino <command> --help` for the full flags. Every row-returning command
takes `--output table` (default), `json`, or `csv`.

## Vector search

The CLI does not embed text — embed your query with your own model and pass the
vector as a JSON array (or `-` for stdin):

```bash theme={null}
infino vector-search docs embedding --vector-file query.json -k 10 --uri file://./data
```

Give the column a vector index when you create the table:
`--vector embedding:384:256:cosine` (`column:dim:centroids:metric`).

## Agent skills

`infino skills install` writes skill files into `~/.claude/skills` so coding
agents (Claude Code, Cursor) can drive the CLI in natural language:

```bash theme={null}
infino skills install
infino skills status
```

This complements the [MCP server](/integrations/mcp): skills are for shell-native
agents, MCP is for tool-calling agents.

## Learn more

* Source, issues, and releases: [github.com/infino-ai/infino-cli](https://github.com/infino-ai/infino-cli)
* Packages: [crates.io](https://crates.io/crates/infino-cli) · [npm](https://www.npmjs.com/package/@infino-ai/infino-cli)