--- title: Support Knowledge Agent description: Build an agentic RAG system that searches Notion, checks Datadog, and manages GitHub issues for support triage --- [View source on GitHub](https://github.com/ComposioHQ/composio/tree/next/docs/examples/support-agent) This cookbook builds an **agentic RAG** system: an interactive CLI agent that triages support issues by pulling context from Notion docs, Datadog monitors, and GitHub issues. It uses scoped sessions, multi-turn chat with streaming, and a structured system prompt. ## Prerequisites * Python 3.10+ * [UV](https://docs.astral.sh/uv/getting-started/installation/) * [Composio API key](https://platform.composio.dev/settings) * [OpenAI API key](https://platform.openai.com/api-keys) ## Project setup Create a new project and install dependencies: ```bash mkdir composio-support-agent && cd composio-support-agent uv init && uv add composio composio-openai-agents openai-agents ``` Add your API keys to a `.env` file: ```bash title=".env" COMPOSIO_API_KEY=your_composio_api_key OPENAI_API_KEY=your_openai_api_key ``` ## Setting up the client `Composio` takes an `OpenAIAgentsProvider` so that tools come back in the format the OpenAI Agents SDK expects. We also import the streaming event types we'll need for real-time output. ../../examples/support-agent/main.py#setup ## Defining the agent The system prompt tells the agent what tools it has and how to behave. It knows about Datadog, Notion, and GitHub, and decides on its own which to use based on the question. ../../examples/support-agent/main.py#agent ## Chat loop with streaming The chat loop creates a session scoped to three toolkits: `datadog`, `notion`, and `github`. The agent only sees tools from these services. `Runner.run_streamed` streams tokens as they arrive so you see the response in real time. Message history is tracked in a list for multi-turn context. ../../examples/support-agent/main.py#chat If a toolkit isn't connected yet, the agent will automatically return an authentication link in its response. The user can complete OAuth and then retry. ## Complete script Here's everything together: ../../examples/support-agent/main.py ## Running the agent ```bash uv run --env-file .env python main.py ``` The agent starts an interactive chat. Type a message and watch the response stream in. Type `quit` to exit. ``` Support Knowledge Agent (type 'quit' to exit) -------------------------------------------------- You: The payments service is returning 500 errors. Can you check what's going on? Agent: I checked Datadog and found an active alert on the payments-api monitor... ``` ## Take it further The agent's scope is defined by its toolkits and system prompt. Swap them to build different support workflows: - **Escalation bot**: add PagerDuty and Slack toolkits so the agent can page on-call engineers and post incident threads automatically - **Customer-facing KB**: replace Datadog with Zendesk, let the agent search help articles and draft replies to open tickets - **Incident timeline**: add Jira and Confluence toolkits so the agent can cross-reference tickets with runbook docs and build a timeline