> **Building with AI coding agents?** Install the authstack plugin with one command. This equips your agent with accurate Scalekit implementation patterns.
>
> **Recommended**:
> ```bash
> npx @scalekit-inc/cli setup
> ```
>
> Global:
> ```bash
> npm install -g @scalekit-inc/cli
> scalekit setup
> ```
>
> Supports Claude Code, Cursor, GitHub Copilot, Codex + skills for 40+ agents.
> Features: full-stack-auth, agent-auth, mcp-auth, modular-sso, modular-scim.
> [Full setup guide](https://docs.scalekit.com/dev-kit/build-with-ai/)

---

# Cognee connector

1. ### Install the SDK

   ```bash frame="terminal"
       npm install @scalekit-sdk/node
       ```
     ```bash frame="terminal"
       pip install scalekit
       ```
     Full SDK reference: [Node.js](/agentkit/sdks/node/) | [Python](/agentkit/sdks/python/)

2. ### Set your credentials

   <AgentKitCredentials />

3. ### Set up the connector

   Register your Cognee credentials with Scalekit so it can authenticate requests on your behalf. You do this once per environment.

   <details>
   <summary>Dashboard setup steps</summary>

   <SetupCogneeSection />

   </details>

4. ### Make your first call

   <QuickstartGenericApikeySection connector="cognee" toolName="cognee_list_datasets" providerName="Cognee" />

## What you can do

Connect this agent connector to let your agent:

- **Recall records** — Search Cognee's knowledge graph by meaning and get back an answer or matching context
- **Improve records** — Enrich a dataset's knowledge graph with new text, or reprocess the existing graph to sharpen later recall
- **Forget records** — Permanently delete a dataset (by name or ID), a single data item, or just its memory graph
- **List datasets** — Discover the dataset names and UUIDs accessible to the connected account
- **List dataset data** — Inspect the individual data items stored in a dataset, with their UUIDs
- **Check status** — Check the processing status of a dataset's ingestion or enrichment pipeline
- **Create dataset** — Provision a new, empty dataset up front by name
**Remember is coming soon:** Cognee's ingest endpoint (`POST /api/v1/remember`) requires a `multipart/form-data` request, which the Scalekit tool proxy doesn't support yet (JSON bodies only). Track backend support in **SK-1178**. Until then, use `cognee_improve` with the `data` field to add text into a dataset.

## Common workflows

<SectionAfterSetupCogneeCommonWorkflows />

## Tool list

Use the exact tool names from the **Tool list** below when you call `execute_tool`. If you're not sure which name to use, list the tools available for the current user first.

<ToolList tools={tools} />

---

## More Scalekit documentation

| Resource | What it contains | When to use it |
|----------|-----------------|----------------|
| [/llms.txt](/llms.txt) | Structured index with routing hints per product area | Start here — find which documentation set covers your topic before loading full content |
| [/llms-full.txt](/llms-full.txt) | Complete documentation for all Scalekit products in one file | Use when you need exhaustive context across multiple products or when the topic spans several areas |
| [sitemap-0.xml](https://docs.scalekit.com/sitemap-0.xml) | Full URL list of every documentation page | Use to discover specific page URLs you can fetch for targeted, page-level answers |