LangGraph
Connect Akto with LangGraph
Overview
LangGraph is a framework for building stateful, multi-actor AI agent applications using graph-based workflows. This integration lets you capture tool calls, agent interactions, and execution traces from your LangGraph applications and send them into Akto for security monitoring and policy enforcement.
Akto supports three integration methods for LangGraph depending on your deployment requirements.
Integration Methods
1. Via LangSmith (Telemetry)
LangGraph natively integrates with LangSmith for observability and tracing. If your LangGraph application already reports traces to LangSmith, you can use Akto's existing LangChain connector to pull that data into Akto — no additional instrumentation required.
Follow the steps in the LangChain connector guide to configure the integration. The same connector works for LangGraph applications traced through LangSmith.
When to use this
Use this method if you want passive observability — collecting execution traces and API traffic after the fact without intercepting live requests.
2. Via Proxy
Route your LangGraph agent's outbound LLM and tool calls through Akto's AI Agent Proxy. This gives you real-time inspection, guardrails enforcement, and response filtering on every request your agent makes — without modifying your application logic.
Refer to the AI Agent Proxy guide for setup instructions.
When to use this
Use this method if you want active enforcement — intercepting and inspecting requests in real time before they reach the LLM or tool.
3. Via Hooks
Coming Soon
Native LangGraph hook-based integration is coming soon in Akto. This will allow you to instrument your LangGraph graphs directly using lifecycle hooks, enabling deep visibility into node-level execution, state transitions, and tool calls without routing traffic through a proxy.
Reach out to us at [email protected] to register your interest.
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