Hermes Agent with Cognee Cloud

Connect Hermes Agent to Cognee Cloud with a drop-in memory provider.

Give Hermes Agent persistent memory backed by your Cognee Cloud tenant with a drop-in memory provider plugin. Each completed turn is stored in Cognee’s session cache and promoted into the permanent knowledge graph at session end — no code required.

1. Install the plugin

Install the plugin from PyPI:

pip install cognee-integration-hermes-agent
cognee-hermes-install      # copies the plugin into $HERMES_HOME/plugins/cognee
hermes memory setup        # select "cognee", then choose remote mode (see step 2)

Once the plugin is accepted into the Hermes plugin catalog, you will also be able to install it with hermes plugins install cognee followed by hermes plugins enable cognee. The full integration guide covers both install paths and how each one updates.

Requires Python 3.10+. The plugin pins cognee==1.6.0 as a pip dependency.

2. Connect to Cognee Cloud

Hermes connects to Cloud in remote mode. At the Mode prompt of hermes memory setup, enter remote, then your tenant URL and API key. Setup defaults to local, and the mode it saves takes precedence over environment variables, so accepting the default keeps Hermes local even after you export the variables below. Alternatively, export them before running setup, so it offers remote as the default. There are no silent fallbacks — if the configured mode fails, the failure surfaces.

export COGNEE_BASE_URL="https://your-tenant.aws.cognee.ai"
export COGNEE_API_KEY="<your-api-key>"

No LLM key is needed in remote mode — your tenant does the knowledge extraction server-side. Setup saves non-secret settings to $HERMES_HOME/cognee.json and secrets to $HERMES_HOME/.env; values in cognee.json beat environment variables, so re-run setup to change the mode or dataset.

3. Run and verify

Run Hermes as usual — memory is captured and recalled automatically:

hermes                  # start a session

During a session, just talk to the agent:

You: Remember that Alice works in engineering.
     (Cognee stores this turn in the session cache)

You: What does Alice do?
     (Hermes recalls from Cognee Cloud memory)

The provider exposes five memory tools to the agent:

• cognee_recall — search your tenant’s knowledge graph, with the conversation’s session id attached
• cognee_remember — persist content into the knowledge graph
• cognee_forget — delete memory, in two phases: the agent lists candidates first, then deletes only the ones you confirm
• cognee_switch_dataset — move the conversation to another dataset on your tenant
• cognee_code_search — query an indexed repository’s code graph

At session end, if COGNEE_IMPROVE_ON_END=true (the default), cognee.improve(...) promotes the session cache into your permanent graph.

Configuration

Variable	Default	Description
COGNEE_BASE_URL	—	Cognee API base URL (enables remote/cloud mode)
COGNEE_API_KEY	—	Cognee service API key
COGNEE_PLUGIN_DATASET	agent_sessions	Dataset name for stored memory (COGNEE_DATASET is a kept alias)
COGNEE_TOP_K	5	Max results per recall
COGNEE_IMPROVE_ON_END	true	Run improve() at session end

The default dataset is shared with Cognee’s other agent plugins (Claude Code, Codex, OpenClaw), so memory written in any of them is recalled in all of them. Set COGNEE_PLUGIN_DATASET to give Hermes a dataset of its own on your tenant.

Manage the plugin with hermes cognee status, hermes cognee setup, hermes cognee config, hermes cognee install, and hermes cognee version (plugin version and update availability). hermes cognee index-repo <git-url> indexes a repository into a deterministic code graph on your tenant — pass a git URL, since a Cloud tenant cannot read a path on your machine.

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Full integration guide

Tools, connection modes, and how it works

Hermes Agent

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