Agent Quickstart

This page helps you equip an AI agent to work with Extend. There are three integration paths, each built for a different kind of agent. Pick the one that matches how yours works.

Pick how your agent will work with Extend

The paths are independent. Set up only what your agent will actually use, and add another path later if its role grows. Whichever you pick, your agent can also read these docs directly with no setup at all.

Connect a chat or tool-calling client over MCP

The fastest path, and the only one with nothing to install: no API key, no CLI, no context files. Connect your client to the hosted server and complete the OAuth browser sign-in when prompted:

https://mcp.extend.ai/mcp

The server exposes the whole platform (parsing, extraction, classification, splitting, PDF editing, workflows, files, webhooks, and evaluations) as tools with run polling and structured errors built in. During sign-in you choose exactly which workspaces the client may use, and whether it can act in Test, Production, or both.

Per-client setup (Cursor, Claude Code, Claude, ChatGPT, VS Code, Codex, Windsurf), the full tool reference, and troubleshooting live on the MCP Server page.

Equip an agent that runs the CLI

For agents that do their work in a shell (one-off document jobs, batch runs, and managing extractors, workflows, or webhooks from the terminal), install the CLI and run the setup wizard:

$
curl -fsSL https://extend.ai/install.sh | sh
$
extend setup

(Prefer Homebrew, npm, or Go? See the CLI installation options.)

The wizard signs you in (through your browser with no API key, or with an API key for headless use), picks your region, and installs the extend-cli agent skill: a SKILL.md generated from the CLI’s own command tree that teaches your harness to drive extend correctly. It lands at ~/.agents/skills/extend-cli/SKILL.md, the cross-client default path, with a symlink into ~/.claude/skills/extend-cli for Claude Code.

For non-interactive environments like CI or a remote agent box, skip the wizard:

$
export EXTEND_API_KEY="sk_xxx"   # from https://dashboard.extend.ai/developers
$
extend skill install

Verify the setup by asking your agent to run a read-only command that spends no credits:

$
extend extractors list

A clean list back means the key, the CLI, and the connection all work.

Equip an agent that writes SDK code

An agent generating application code needs two things: an API key for the code it writes, and Extend’s platform context file so that code is correct on the first try. The context file is a compact brief on the API, SDKs, schema rules, sync-vs-async patterns, webhooks, and error handling.

First, create a key on the Developers dashboard and export it where the agent’s code will run:

$
export EXTEND_API_KEY="sk_xxx"

SDK clients read the key from the environment (or accept it as a constructor argument) and set the auth header and API version for you.

Then install the context file as a skill named extend-platform. This mirrors where the CLI installs its own skill, so it works across every project and harness:

$
mkdir -p ~/.agents/skills/extend-platform ~/.claude/skills
$
curl -fsSL https://docs.extend.ai/agents.md -o ~/.agents/skills/extend-platform/SKILL.md
$
ln -sfn ~/.agents/skills/extend-platform ~/.claude/skills/extend-platform   # Claude Code reads ~/.claude/skills

To scope it to a single repo, use the same layout under the project root (.agents/skills/extend-platform plus a .claude/skills symlink) instead of ~.

The official SDKs cover four languages. Python, TypeScript, and Java ship polling helpers (create_and_poll / createAndPoll) and built-in webhook signature verification; Go has neither, so an agent writing Go should poll and verify signatures manually.

$
pip install extend-ai

Let your agent read the docs

No setup required. Every page of these docs is directly readable by an agent:

• Index: https://docs.extend.ai/llms.txt: a curated map of every doc page.
• Any page as Markdown: append .md to a doc URL (e.g. https://docs.extend.ai/extraction/schema.md) for clean, token-cheap content.

Mention these in your project instructions or add them to your agent’s allowed-fetch list so it reaches for the docs instead of guessing. Agents on the MCP path get this for free through the search_documentation and get_documentation tools.

Where to go next