Integrations

Connect AI agents, coding tools, and automation platforms to Cognee memory

The Integrations page (route /integrations, under the CONNECT section of the sidebar alongside API Keys) is the in-product hub for wiring external tools into your Cognee memory. Each card opens a step-by-step modal that injects your tenant’s live base URL and API key into copy-on-click code blocks, so the snippets are ready to paste without editing.

Everything in these flows runs locally on your machine — nothing is sent to Cognee. When a step writes to an existing config file, the previous version is backed up to .bak before being overwritten.

The page has three sections, in order: Agents (“Connect your AI agents and coding tools to Cognee for persistent memory”), Automation platforms (“Give your automation workflows access to Cognee memory via MCP”), and Data sources (“Connect the tools your team already uses as data sources for your brains”).

Mac / Windows

A Mac / Windows toggle sits in the top-right corner of three surfaces, and defaults to Mac everywhere:

• The setup modals on this page, on the four OS-aware cards: Claude Code, Codex, OpenClaw, and API / MCP.
• The connect modal that opens from a Claude Code, Codex, Openclaw, or API / MCP card on the dashboard. The toggle is inside the modal, not on the card. The Company Brain card opens the document upload flow instead, which has no toggle.
• The agent connection steps in onboarding.

Flipping it to Windows rewrites the commands shown on screen, the commands copied to your clipboard, and the step text that says where to run them:

What changes	Mac / Linux	Windows (PowerShell)
Where to run it (step title and copy)	“Open Terminal"	"Open PowerShell”
Plugin credentials — Claude Code and Codex write ~/.cognee/.env	mkdir -p + printf + chmod 600	New-Item -ItemType Directory -Force + Set-Content + icacls
Shell credentials — Openclaw and API / MCP export into the session	export COGNEE_BASE_URL="…"	$env:COGNEE_BASE_URL = "…"
Skill file path (Openclaw)	~/.openclaw/skills/cognee/SKILL.md	$env:USERPROFILE\.openclaw\skills\cognee\SKILL.md
Writing a skill file	mkdir -p + heredoc	New-Item -ItemType Directory -Force + Set-Content
REST call (dashboard API / MCP card)	curl (multi-line, backslash continuations)	curl.exe (single line)

Your credentials and the skill content itself are identical on both — only the shell syntax around them changes. The credentials file also ends up locked to your user on both: chmod 600 on Mac, icacls stripping the inherited permissions on Windows.

The toggle does not reach every step. On this page, the OpenClaw AGENTS.md step and the API / MCP REST and skill steps stay in bash form even with the toggle set to Windows, and the cards without a toggle at all — Claude Desktop, Cursor, VS Code, Gemini CLI, Cline, Hermes Agent — are written for macOS and Linux throughout. On Windows, translate those with the table above: the config-file paths are the ones that differ, and where a card tells you to run which uvx, run Get-Command uvx instead.

Agents

Agent cards come in three styles depending on how the tool reads memory.

Plugin-based

Coding agents (CTA Connect via plugin) install the cognee-memory plugin, which hooks into the agent’s lifecycle to capture and recall memory automatically — no code:

Claude Code

claude plugin marketplace add topoteretes/cognee-integrations
claude plugin install cognee-memory@cognee

Codex

codex features enable hooks
codex plugin marketplace add topoteretes/cognee-integrations --ref main
codex plugin add cognee@cognee

See the dedicated Claude Code and Codex integration pages for full configuration.

Prompt-based

This card (CTA Connect via prompts) writes a memory instruction file into your workspace so the agent learns to use Cognee through its system prompt:

Tool	File written
OpenClaw	~/.openclaw/workspace/AGENTS.md

Prompt-based flows read the COGNEE_BASE_URL environment variable. The instruction file teaches the agent to recall context before answering and to remember new facts afterward.

For Claude Code, the marketplace plugin is the recommended direct memory path. The full setup lives in Claude Code Integration; the key install commands are:

claude plugin marketplace add topoteretes/cognee-integrations
claude plugin install cognee-memory@cognee

Use COGNEE_BASE_URL and COGNEE_API_KEY for Cognee Cloud or a remote server. If those are missing, the plugin uses local mode and needs only LLM_API_KEY.

MCP-based

These cards (CTA Connect via MCP) register Cognee as an MCP server in the client’s config. Cognee runs via uvx (requires uv) — no separate install. The Claude Desktop, Cursor, and Gemini CLI cards are guided walkthroughs: they step you through installing uv, opening the client’s MCP config file, merging in the Cognee server block (shown as an annotated preview so you can copy just the highlighted fragment into your existing file), and restarting the client to test.

Most clients read an mcpServers entry that passes credentials as environment variables:

{
  "mcpServers": {
    "cognee": {
      "command": "uvx",
      "args": ["cognee-mcp"],
      "env": {
        "COGNEE_BASE_URL": "https://your-tenant.aws.cognee.ai",
        "COGNEE_API_KEY": "your-api-key"
      }
    }
  }
}

Each client reads its config from a different location:

Client	Config location
Claude Desktop	Open Settings → Developer → Edit Config to create/open claude_desktop_config.json
Cursor	~/.cursor/mcp.json (use Add Custom MCP to scaffold it)
Hermes Agent	~/.hermes/config.yaml (YAML)
Gemini CLI	~/.gemini/settings.json
Cline	VS Code Cline sidebar → MCP Servers

The Claude Desktop flow passes credentials as command-line arguments rather than environment variables — it pins cognee-mcp@latest and appends --api-url and --api-token. Merge only the "cognee" entry into any mcpServers block you already have, then fully quit (⌘Q / quit from the tray on Windows) and reopen Claude Desktop. If Claude never calls a cognee tool, it usually can’t find uvx on its PATH — run which uvx (Get-Command uvx on Windows) and use that absolute path as the command value.

Gemini CLI

Gemini CLI has no UI for adding an MCP server, so its card walks you through editing ~/.gemini/settings.json yourself and shows the complete file you should end up with — your tenant URL and API key included, and the "cognee" entry highlighted — so nothing is hidden inside a copied command. Like Claude Desktop, it passes credentials as --api-url and --api-token arguments to cognee-mcp@latest rather than as environment variables:

1. Install uv

   brew install uv, or curl -LsSf https://astral.sh/uv/install.sh | sh. This is what provides uvx.

2. Open ~/.gemini/settings.json

   If the file or the ~/.gemini folder doesn’t exist yet, run gemini once to create them, or create the file yourself.

3. Add the Cognee server and save

   On a new or empty file, paste the whole block the card shows (the copy button copies all of it). If you already have an mcpServers block, add only the highlighted "cognee" entry inside it.

4. Confirm it connected

   Start gemini, then type /mcp in the session — cognee should be listed with its tools. Then ask “What do you know from cognee?”.

If /mcp doesn’t list cognee, Gemini usually can’t find uvx on its PATH. Run which uvx and use that absolute path as the "command" value in settings.json.

Extension-based

The VS Code card (CTA Connect via extension) uses the “Cognee — Project Memory” extension from the VS Code Marketplace instead of an MCP config file. After installing it:

1. Run Cognee: Set Up from the Command Palette and paste your endpoint, then your API key (stored in your OS keychain, not settings). A health check confirms the connection.
2. Use the core commands from the Command Palette under Cognee:
   • Cognee: Remember Selection — store the selected code (or the whole file) in this repo’s memory.
   • Cognee: Ask My Project Memory — ask a question and get answers with clickable citations.
   • Cognee: Index Workspace — bulk-ingest the whole repository at once.

API / MCP

The Connect via API or MCP card is for any tool not covered above. It gives you a curl recall example and the option to install the generic Cognee skill:

curl -X POST https://your-tenant.aws.cognee.ai/api/v1/recall \
  -H "X-Api-Key: $COGNEE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query": "What do you know from cognee?"}'

Automation platforms

Bring Cognee memory into your workflow tools (CTA Connect via node / Connect via plugin):

Platform	How
n8n	Install the community node package n8n-nodes-cognee, then add a Cognee API credential.
Dify	Install the Marketplace plugin by topoteretes.

For Dify, the base URL must include the /api suffix (for example https://your-tenant.aws.cognee.ai/api).

Credentials and environment variables

The flows export these variables:

Variable	Used by
COGNEE_BASE_URL	Prompts, skills, the Claude Code plugin, and MCP servers. If missing, the client drops into local mode.
COGNEE_API_KEY	Cloud and remote clients, for authentication. The local Claude Code plugin can auto-mint one if absent.

Setups now use COGNEE_BASE_URL as the single endpoint variable — the older COGNEE_SERVICE_URL alias is no longer exported by these flows.

Authentication uses the X-Api-Key header (not Bearer). To confirm a key and URL work, run a health ping against the datasets endpoint:

curl https://your-tenant.aws.cognee.ai/api/v1/datasets/ \
  -H "X-Api-Key: $COGNEE_API_KEY"

A 200 means the connection is good, 401 means the key is wrong, and 404 or a 5xx means the URL is wrong or the service is unavailable.

How memory works once connected

Connected tools read and write memory through two endpoints.

Recall (POST /api/v1/recall) retrieves context. The search_type parameter controls how results are assembled:

search_type	Behavior
HYBRID_COMPLETION	Default — combines graph and chunk retrieval.
GRAPH_COMPLETION	Answers from the knowledge graph.
CHUNKS	Returns raw matching text chunks.
GRAPH_SUMMARY_COMPLETION	Summarized graph-based answer.

Remember (POST /api/v1/remember/entry) stores a fact. Tie related entries together with a shared session_id:

{
  "entry": { "type": "qa", "question": "...", "answer": "..." },
  "dataset_name": "default_dataset",
  "session_id": "..."
}

The default dataset name is default_dataset.

Use /remember/entry for inline text. The plain /remember endpoint requires a file upload and returns 422 for inline text.

Verify the connection

After running any flow, verify the integration by asking the connected agent:

What do you know from cognee?

If memory is wired up correctly, the agent recalls context from your knowledge graph. The final step of each flow includes a Go to Sessions → button that takes you to your live Sessions.

Debug plugin hooks

When a plugin-based agent does not capture or recall memory, debug the layers separately.

Layer	What to check
Hooks	The agent must call the Cognee plugin on prompt submit, tool use, stop, compaction, and session end. For Codex, run codex features enable hooks and trust the Cognee hooks in /hooks if prompted. For Claude Code, confirm the startup message says “Cognee Memory Connected”.
Backend	Cloud and remote mode need COGNEE_BASE_URL and COGNEE_API_KEY. Local mode needs LLM_API_KEY so the plugin-managed local Cognee API can start again after it was stopped.
Session	A resumed terminal only continues the same live session when the session id and dataset match. Set COGNEE_SESSION_ID and keep COGNEE_PLUGIN_DATASET unchanged when you want a restart to keep writing to the same session.

Hooks do not replay events that happened while they were disabled, untrusted, or unable to reach Cognee. After changing hook trust, credentials, dataset, or session id, restart the agent so its startup hook can initialize the new state.

For the most reliable graph sync, exit the agent normally. Claude Code users can also run /cognee-memory:cognee-sync before closing. If the process is killed, recent session cache entries may exist, but the final session-to-graph sync may not have run yet.

Data sources

The Data sources section lists connectors that pull the tools your team already uses into your brains — one connection per workspace, shared with everyone. Slack is the first live connector: Connect on its card opens a dialog that connects your workspace, and a connected card shows the connection’s status and channel/sync health, with Manage (or Reconnect, when the connection needs attention) opening the same dialog.

Below it, a More data sources section (“Not live yet — tell us which ones to prioritize.”) lists twenty-two upcoming connectors: Notion, Google Drive (Docs, Sheets, and Slides), Confluence, GitHub, Gmail, Jira, Linear, Granola, Asana, monday.com, Figma, HubSpot, Intercom, Box, Canva, PostHog, Stripe, Vercel, MotherDuck, Xero, lemlist, and Workable. A Search data sources field beside that heading filters the cards by name or description as you type; if nothing matches, the section shows No data sources match ”.” with a Request it link that opens a pre-filled email to [e-mail].

These upcoming connectors are not built yet — clicking one opens a Coming soon dialog with a Get notified once live button that registers your interest so we can prioritize what to build next. A footer link (Let us know) emails [e-mail] if you want to request a source directly.

Self-hosted Cognee deployments run their own, separate Slack app against their own backend — setup and usage are covered in the Slack integration guide. To bulk-load data from these tools in code today (for example Slack channel history via dlt’s slack_source), see the dlt integration.

Related

Sessions

Inspect the live memory your connected tools read and write.

API Keys

Create and manage the keys these integrations authenticate with.

Cloud SDK

Call recall and remember programmatically from your own code.

Cloud MCP

Details on the Cognee MCP server and its tools.