LangGraph

LangGraph nodes call a LangChain chat model — configure that model once and every node that uses it is tracked. Point ChatOpenAI at Toolken’s gateway, add X-Toolken-Key to default_headers, and spend appears in your dashboard broken down by agent.

Get your two keys

You need two keys:

Key	Where to get it	Looks like
Toolken key	Dashboard, under API Keys	`tk_live_...`
Provider key	Your OpenAI account (or whichever provider you use)	`sk-...`

Toolken forwards your provider key to the upstream model provider untouched and never stores it.

Build the model

Use ChatOpenAI from langchain_openai. Set base_url to Toolken’s gateway and pass your keys in default_headers:

from langchain_openai import ChatOpenAI

model = ChatOpenAI(
    base_url="https://gateway.toolken.ai/v1",
    api_key="sk-...",          # your provider key (BYOK), forwarded untouched
    default_headers={
        "X-Toolken-Key": "tk_live_...",
        "X-Toolken-Metadata-Agent": "research-agent",
    },
)

X-Toolken-Metadata-Agent labels this model’s traffic in the dashboard. Use any string that identifies the graph or workflow.

Use the model in your graph nodes

Pass model into whichever nodes call the LLM. A simple invoke pattern looks like:

from langgraph.graph import StateGraph, MessagesState

def call_model(state: MessagesState):
    response = model.invoke(state["messages"])
    return {"messages": response}

builder = StateGraph(MessagesState)
builder.add_node("agent", call_model)

No changes to your graph structure, edges, or state schema are needed.

Confirm in your dashboard

Run your graph. Within seconds, calls appear in the Toolken dashboard grouped under the research-agent agent. Cost, token usage, and latency are captured for every node invocation.

To attribute spend per agent or per node, create one ChatOpenAI instance per logical role and give each a distinct X-Toolken-Metadata-Agent value. For example, a "planner-agent" model and a "summarizer-agent" model each show up as separate line items in the dashboard, so you can see exactly which part of your graph is driving cost.

CrewAI

Configure Toolken for CrewAI agents with the built-in LLM class.

Providers & Routing

One gateway URL, many providers, your own keys.

Getting Started

Observability

Providers & Routing

Rate Limits

Integrations

Use cases

Next

CrewAI

Providers & Routing

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CrewAI

Providers & Routing

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