IMPLEMENTATION
Call this tool
Connect a user's Anthropic (Claude) account once, then configure and run Chat from your backend or agent.
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: "anthropic-chat",
externalUserId: "{external_user_id}", // any stable ID for this user in your system
configuredProps: {
anthropic: { authProvisionId: "apn_xxxxxxx" },
model: "Model",
userMessage: "User Message",
},
})
console.log(result)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": "anthropic-chat",
"configured_props": {
"anthropic": { "authProvisionId": "apn_xxxxxxx" },
"model": "Model",
"userMessage": "User Message"
}
}'// 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": "anthropic",
},
},
},
)
const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)
const { tools } = await mcp.listTools()
// listTools() hands your model this tool's input schema, so it can
// fill the arguments itself:
const result = await mcp.callTool({
name: "anthropic-chat",
arguments: {
model: "Model",
userMessage: "User Message",
},
})SCHEMA
Inputs
Pipedream supplies the connected account. Your application provides the operation-specific values below. Dynamic inputs are resolved against that user's account.
| Property | Type | Description |
|---|---|---|
model Model | string | Select the model to use. See the documentation for more information Required Dynamic |
userMessage User Message | string | The user messages provide instructions to the assistant Required |
messages Prior Message History | string[] | All relevant information must be supplied via the conversation. You can provide an array of messages from prior conversations here always beginning with the human message. Optional |
temperature Temperature | string | Optional. Amount of randomness injected into the response. Ranges from 0 to 1. Use temp closer to 0 for analytical / multiple choice, and temp closer to 1 for creative and generative tasks. Optional |
topK Top K | integer | Only sample from the top K options for each subsequent token. Used to remove long tail low probability responses. Optional |
topP Top P | string | Does nucleus sampling, in which we compute the cumulative distribution over all the options for each subsequent token in decreasing probability order and cut it off once it reaches a particular probability specified. Optional |
maxTokensToSample Maximum Tokens To Sample | integer | A maximum number of tokens to generate before stopping. Required |
REFERENCE
Tool details
Behavior hints are published with the component in the Pipedream registry and surface as MCP tool annotations, so an agent can reason about a tool before it calls it.
- Registry key
- anthropic-chat
- Version
- 0.2.2
- App
- Anthropic (Claude)
- Authentication
- API key
- Read-only
- No
- Destructive
- No
- Open world
- Yes
- Source
- View on GitHub ↗