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How to integrate Dialogflow using MCP

Detect intents and manage conversational agents. This guide creates an MCP server from Arthur's Dialogflow template — tools preconfigured against https://dialogflow.googleapis.com — and finishes by sharing the server's MCP swagger documentation.

Steps

  1. Open the Secrets vault and create a secret named DIALOGFLOW_API_KEY holding your access token. Authenticate with a Google OAuth access token from Application Default Credentials, a service account, or gcloud. The caller needs appropriate Dialogflow IAM roles and cloud-platform or dialogflow scope.

    Open the Secrets vault to store the Dialogflow credential before using the template

    Start the New secret wizard

    Name the secret DIALOGFLOWAPIKEY — servers reference it by this name

  2. Go to the REST API Templates gallery and search for Dialogflow.

    Record what the credential is for so it stays recognizable

    Continue to the protected value step

  3. Click Use template on the Dialogflow card to open the server-creation dialog.

    Enter the credential value — a demo value here; use your real key when adopting the integration

    Review the generated secret reference syntax

  4. Review the server name and select DIALOGFLOW_API_KEY in the credential field — the dialog only accepts vault secrets, and it lists every tool that will be created.

    Store the DIALOGFLOWAPIKEY secret in the vault

    Open the REST API template gallery

    Search the gallery for the Dialogflow integration

  5. Click Create server. Arthur creates the server, applies the authentication, and generates all the tools.

    Open the Dialogflow template with its preconfigured tools

    Name the server after the integration it provides

    Pick the DIALOGFLOWAPIKEY secret from the vault suggestions

    Select the stored credential

    Create the Dialogflow server with its preconfigured tools

  6. Open the server's Tools tab to review the generated tools.

    Review the tools generated from the Dialogflow template

  7. Open the server's Connect section and click Share the MCP swagger documentation — Arthur generates the public documentation link and QR code for this server.

    Open the server's Connect section, where the MCP endpoint and its documentation live

    Open the MCP swagger documentation share panel

    Show the generated swagger documentation link and QR code for this server

Confirm it worked

The server appears with 2 preconfigured tool(s): detect_intent, list_intents. The Connect section offers the MCP swagger documentation — a shareable page with setup instructions for any AI client.

Good to know

  • Send end-user expressions to a Dialogflow ES agent and receive matched intents, parameters, actions, and configured responses. Requires a Google Cloud project, the Dialogflow API, IAM permissions, and an OAuth access token.
  • This integration requires a credential (bearer). Get one at https://console.cloud.google.com/.
  • Official API documentation: https://docs.cloud.google.com/dialogflow/es/docs/reference/rest/v2-overview
  • Editing a tool later never changes the template — templates are starting points, and the server is fully yours after creation.

Related

Tutorial video