Connect LangChain & LangGraph

from canopy_ai.langchain import to_langchain_tools returns ready-to-use StructuredTool instances. Pass them straight to LangGraph's create_react_agent or any LangChain agent that accepts a tool list.

Step 1 — Connect your agent in the dashboard

Canopy is bring-your-own-agent. This step doesn't create the agent itself — you've already built that, or are about to. It registers a Canopy-side record that pairs your agent with a spending policy and gives you an agt_… ID to use in your code.

Sign in at trycanopy.ai and go to Agents → Connect agent. Give the agent a name and pick (or create) a policy. The policy controls the spend cap, recipient allowlist, and approval threshold every payment from this agent will be evaluated against.

Step 2 — Copy your credentials

You need two values in your code:

• Org API key (ak_live_… or ak_test_…) — from Settings → API Keys. Copy it the moment you create it; the plaintext is shown only once.
• Agent ID (agt_…) — from the agent's detail page in /dashboard/agents.

Step 3 — Install the package

pip install 'canopy-ai[langchain]' langgraph langchain-openai

Step 4 — Set your environment variables

CANOPY_API_KEY=ak_live_xxxxxxxxxxxxxxxx
CANOPY_AGENT_ID=agt_xxxxxxxx

Use a .env file locally and your platform's secret manager in production. Never commit credentials.

Step 5 — Connect in your agent code

Paste the snippet below into your existing LangGraph agent.

# 1. Add to your .env:
# CANOPY_API_KEY=ak_live_xxxxxxxxxxxxxxxx

# 2. In your agent code:
import os
from canopy_ai import Canopy
from canopy_ai.langchain import to_langchain_tools
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

canopy = Canopy(
    api_key=os.environ["CANOPY_API_KEY"],
    agent_id="agt_xxxxxxxx",
)

agent = create_react_agent(
    ChatOpenAI(model="gpt-4o"),
    tools=to_langchain_tools(canopy),
)
agent.invoke({
    "messages": [{"role": "user", "content": "Send 10 cents to 0x1234..."}],
})

Step 6 — Verify the connection

Run your agent once. As soon as Canopy receives a request from it, the dashboard flips the agent to connected and shows the first event captured. If nothing happens after a minute, see Troubleshooting.

Install

canopy_ai.langchain requires the optional dep langchain-core. Install with pip install 'canopy-ai[langchain]'.

Async LangGraph

For async workflows (FastAPI, asyncio agent loops), use AsyncCanopy instead — to_langchain_tools(async_canopy) detects the async executors and binds the coroutine= argument on each StructuredTool.

Where to go next

• Payment outcomes — what the agent gets back when a payment succeeds, pends, or is denied
• Python SDK reference — to_langchain_tools and other helpers