CONNECT APP
Build with Chat Data
Data Analytics
- API key
MCP
Give your agent Chat Data tools
Every Chat Data action is exposed as an MCP tool on Pipedream's remote server. Point a client at it with your end user's ID and Connect resolves that user's Chat Data account for each tool call — you store no tokens.
// accessToken: mint a short-lived token with the Connect SDK — see the MCP guide
const transport = new StreamableHTTPClientTransport(
new URL("https://remote.mcp.pipedream.net/v3"),
{
requestInit: {
headers: {
Authorization: `Bearer ${accessToken}`,
"x-pd-project-id": "{project_id}",
"x-pd-environment": "production",
"x-pd-external-user-id": "{external_user_id}", // any stable ID for this user in your system
"x-pd-app-slug": "chat_data",
},
},
},
)
const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)
const { tools } = await mcp.listTools()
// e.g. run Create Chatbot:
const result = await mcp.callTool({
name: "chat_data-create-chatbot",
arguments: {
chatbotName: "Chatbot Name",
sourceText: "Source Text",
},
})# access_token: mint a short-lived token with the Connect SDK — see the MCP guide
headers = {
"Authorization": f"Bearer {access_token}",
"x-pd-project-id": "{project_id}",
"x-pd-environment": "production",
"x-pd-external-user-id": "{external_user_id}", # any stable ID for this user in your system
"x-pd-app-slug": "chat_data",
}
async with streamablehttp_client("https://remote.mcp.pipedream.net/v3", headers=headers) as (read, write, _):
async with ClientSession(read, write) as session:
await session.initialize()
tools = await session.list_tools()
# e.g. run Create Chatbot:
result = await session.call_tool("chat_data-create-chatbot", {
"chatbotName": "Chatbot Name",
"sourceText": "Source Text",
})API PROXY
Call the Chat Data API directly
For an endpoint with no pre-built tool, the Connect proxy forwards your request to the Chat Data API with the connected user's credentials attached. You store no tokens and write no refresh logic.
const resp = await pd.proxy.get({
externalUserId: "{external_user_id}", // any stable ID for this user in your system
accountId: "apn_xxxxxxx",
url: "https://api.chat-data.com/api/v2/current-plan",
})
// Any allowed Chat Data endpoint works here. Pipedream attaches the
// connected account's credentials to the outgoing request.# The path segment is the target URL, URL-safe base64 encoded:
# https://api.chat-data.com/api/v2/current-plan
curl "https://api.pipedream.com/v1/connect/{project_id}/proxy/aHR0cHM6Ly9hcGkuY2hhdC1kYXRhLmNvbS9hcGkvdjIvY3VycmVudC1wbGFu?external_user_id={external_user_id}&account_id=apn_xxxxxxx" \
-H "Authorization: Bearer {access_token}" \
-H "x-pd-environment: production"SDK
Run Chat Data actions from your backend
Connect a user's Chat Data account once, then run Create Chatbot on their behalf from your own code — TypeScript, Python, or plain HTTP.
import { PipedreamClient } from "@pipedream/sdk"
const pd = new PipedreamClient({
projectId: process.env.PIPEDREAM_PROJECT_ID!,
clientId: process.env.PIPEDREAM_CLIENT_ID!,
clientSecret: process.env.PIPEDREAM_CLIENT_SECRET!,
projectEnvironment: "production",
})
const result = await pd.actions.run({
id: "chat_data-create-chatbot",
externalUserId: "{external_user_id}", // any stable ID for this user in your system
configuredProps: {
chat_data: { authProvisionId: "apn_xxxxxxx" },
chatbotName: "Chatbot Name",
sourceText: "Source Text",
},
})from pipedream import Pipedream
pd = Pipedream(
client_id="{oauth_client_id}",
client_secret="{oauth_client_secret}",
project_id="{project_id}",
project_environment="production",
)
result = pd.actions.run(
id="chat_data-create-chatbot",
external_user_id="{external_user_id}", # any stable ID for this user in your system
configured_props={
"chat_data": {"authProvisionId": "apn_xxxxxxx"},
"chatbotName": "Chatbot Name",
"sourceText": "Source Text",
},
)curl -X POST https://api.pipedream.com/v1/connect/{project_id}/actions/run \
-H "Content-Type: application/json" \
-H "X-PD-Environment: production" \
-H "Authorization: Bearer {access_token}" \
-d '{
"external_user_id": "{external_user_id}",
"id": "chat_data-create-chatbot",
"configured_props": {
"chat_data": { "authProvisionId": "apn_xxxxxxx" },
"chatbotName": "Chatbot Name",
"sourceText": "Source Text"
}
}'TOOLS
Chat Data actions
On-demand operations your product or agent can configure and run on behalf of a connected user.
-
Create Chatbot
actionCreate a chatbot with the specified properties. See the documentationWritev0.0.2 -
Delete Chatbot
actionDelete a chatbot with the specified ID. See the documentationWritev0.0.2 -
Get Chatbot Status
actionGet status of the Chatbot with the specified ID. See the documentationRead-onlyv0.0.2
EVENTS
Chat Data triggers
Event sources your backend can deploy for users and receive through a webhook.
No Chat Data triggers are available yet.
MULTI-APP
Use Chat Data with other popular apps
Most products don't stop at one integration. Pair Chat Data with the other apps your users rely on, and ship use cases that span both.
- App slug
- chat_data
- Authentication
- API key
- Categories
- Data Analytics
- Actions
- 3
- Triggers
- 0
- API proxy
- Available