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Flash (by Velora AI) is an AI copilot for product and growth leaders.

Artificial Intelligence (AI)

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MCP

Give your agent Flash (by Velora AI) tools

Every Flash (by Velora AI) 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 Flash (by Velora AI) account for each tool call — you store no tokens.

Pipedream Connect

// 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": "flash_by_velora_ai",
      },
    },
  },
)

const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)

const { tools } = await mcp.listTools()

// e.g. run Add Feedback:
const result = await mcp.callTool({
  name: "flash_by_velora_ai-add-feedback",
  arguments: {
    feedback: "Feedback",
    title: "Title",
  },
})

# 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": "flash_by_velora_ai",
}

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 Add Feedback:
        result = await session.call_tool("flash_by_velora_ai-add-feedback", {
            "feedback": "Feedback",
            "title": "Title",
        })

MCP guide →

API PROXY

Call the Flash (by Velora AI) API directly

For an endpoint with no pre-built tool, the Connect proxy forwards your request to the Flash (by Velora AI) API with the connected user's credentials attached. You store no tokens and write no refresh logic.

Pipedream Connect

const resp = await pd.proxy.get({
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  accountId: "apn_xxxxxxx",
  url: "https://flash-api.velora.ai/v1/api/add-feedback",
})

// Any allowed Flash (by Velora AI) 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://flash-api.velora.ai/v1/api/add-feedback

curl "https://api.pipedream.com/v1/connect/{project_id}/proxy/aHR0cHM6Ly9mbGFzaC1hcGkudmVsb3JhLmFpL3YxL2FwaS9hZGQtZmVlZGJhY2s?external_user_id={external_user_id}&account_id=apn_xxxxxxx" \
  -H "Authorization: Bearer {access_token}" \
  -H "x-pd-environment: production"

API proxy guide →

SDK

Run Flash (by Velora AI) actions from your backend

Connect a user's Flash (by Velora AI) account once, then run Add Feedback on their behalf from your own code — TypeScript, Python, or plain HTTP.

Pipedream Connect

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: "flash_by_velora_ai-add-feedback",
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  configuredProps: {
    flash_by_velora_ai: { authProvisionId: "apn_xxxxxxx" },
    feedback: "Feedback",
    title: "Title",
  },
})

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="flash_by_velora_ai-add-feedback",
    external_user_id="{external_user_id}",  # any stable ID for this user in your system
    configured_props={
        "flash_by_velora_ai": {"authProvisionId": "apn_xxxxxxx"},
        "feedback": "Feedback",
        "title": "Title",
    },
)

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": "flash_by_velora_ai-add-feedback",
    "configured_props": {
      "flash_by_velora_ai": { "authProvisionId": "apn_xxxxxxx" },
      "feedback": "Feedback",
      "title": "Title"
    }
  }'