Google Datastream MCP Server

Interact with your Google Cloud Datastream resources using natural language commands.

Tools

Last Updated

Jun 14, 2026

What is the Google Datastream MCP Server?

The Google Datastream MCP server gives AI agents structured, permission-aware access to Google Datastream through the Model Context Protocol. With 10 pre-built actions, agents can read, create, and update Google Datastream data on behalf of authorized users.

Willow ships the Google Datastream MCP server as part of an enterprise control plane. Every call runs behind SSO (Okta, Azure AD), enforces RBAC and least-privilege at runtime, writes to a full audit trail, and integrates with Splunk and Loki for SIEM visibility. Connect from Claude Desktop, Claude Code, Cursor, ChatGPT, VS Code, n8n, or any custom agent. Install once, distribute org-wide, and see exactly how Google Datastream is being used by every AI agent in your stack.

Tools

get_operation

Gets the status of a long-running operation. ***Usage*** Some tools (for example, `run_stream`) return a long-running operation. You can use this tool to get the status of the operation. It can be called repeatedly until the operation is complete. **Parameters** * `name`: The name of the operation to get. * `name` should be the name returned by the tool that initiated the operation. * `name` should be in the format of: `projects/{project}/locations/{location}/operations/{operation}`. **Returns** * An `Operation` object that contains the status of the operation. * If the operation is not complete, the response will be empty. Do not check more than every ten seconds. * If the operation is complete, the response will contain either: * A `response` field that contains the result of the operation and indicates that it was successful. * A `error` field that indicates any errors that occurred during the operation.

list_connection_profiles

Lists connection profiles in a given project and location. For example: { parent: "projects/my-project/locations/us-central1" create_time_after: 2025-10-02T10:15:33Z create_time_before: 2025-10-03T00:00:00Z display_name: bookstore page_size: 100 } will return up to 100 connection profiles in `projects/my-project/locations/us-central1` that were created on or after 2025-10-02T10:15:33 UTC and before 2025-10-03T00:00:00 UTC, and have "bookstore" in their display name.

list_streams

Lists streams in a given project and location. For example: { parent: "projects/my-project/locations/us-central1" create_time_after: 2025-10-02T10:15:33Z create_time_before: 2025-10-03T00:00:00Z display_name: bookstore page_size: 100 running: true } will return up to 100 running streams in `projects/my-project/locations/us-central1` that were created on or after 2025-10-02T10:15:33 UTC and before 2025-10-03T00:00:00 UTC, and have "bookstore" in their display name.

get_stream

Get details of the stream specified by the provided resource 'name' parameter. * The resource 'name' parameter is in the form: 'projects/{project name}/locations/{location}/streams/{stream name}', for example: 'projects/my-project/locations/us-central1/streams/my-streams'.

run_stream

Starts an already created stream, specified by the provided resource 'name' parameter. **Parameters** * 'name': The resource name of the stream to start. * 'name' should be in the format of: 'projects/{project name}/locations/{location}/streams/{stream name}', for example: 'projects/my-project/locations/us-central1/streams/my-streams'. * 'force': Whether to run the stream without running prior configuration verification. The default is 'false'. **Returns** * This tool returns a long-running operation. Use the 'get_operation' tool with the returned operation name to poll its status until it completes. Operation may take several minutes; do not check more often than every ten seconds.

delete_stream

Deletes a stream, specified by the provided resource 'name' parameter. * The resource 'name' parameter is in the form: 'projects/{project name}/locations/{location}/streams/{stream name}', for example: 'projects/my-project/locations/us-central1/streams/my-streams'. * This tool returns a long-running operation. Use the 'get_operation' tool with the returned operation name to poll its status until it completes. Operation may take several minutes; do not check more often than every ten seconds.

list_stream_objects

Lists stream objects in a given stream. * Parent parameter is in the form 'projects/{project name}/locations/{location}/streams/{stream name}', for example: 'projects/my-project/locations/us-central1/streams/my-stream'. * Not all the details of the stream objects are returned. * To get the full details of a specific stream object, use the 'get_stream_object' tool.

get_stream_object

Get details of the stream object specified by the provided resource 'name' parameter. * The resource 'name' parameter is in the form: 'projects/{project name}/locations/{location}/streams/{stream name}/objects/{stream object name}', for example: 'projects/my-project/locations/us-central1/streams/my-stream/objects/my-stream-object'.

lookup_stream_object

Lookup a stream object by its source object identifier. **Parameters:** * The 'parent' parameter is the name of the stream in the form: 'projects/{project name}/locations/{location}/streams/{stream name}', for example: 'projects/my-project/locations/us-central1/streams/my-stream'. * The 'source_object_identifier' parameter is the source database object identifier. Different source databases have different identifier formats. Examples: * Oracle, PostgreSQL, SQL Server and Spanner databases the identifier is 'schema' and 'table'. * MySQL databases the identifier is 'database' and 'table'.

list_static_ips

Lists static IP addresses of the provided resource name that need to be allowlisted by the customer when using the static-IP connectivity method. Returns up to 100 IP addresses. * The resource 'name' parameter is in the form 'projects/{project name}/locations/{location}', for example: 'projects/my-project/locations/us-central1'.

Customize Tools

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Set Up Your Google Datastream MCP Server in Minutes

Add the following configuration to your MCP client. Authentication is handled via OAuth. Compatible with Claude Desktop, Claude Code, Cursor, ChatGPT, VS Code, n8n, and any MCP-compatible agent.

Claude Desktop

claude_desktop_config.json

{
  "mcpServers": {
    "willow-google-datastream": {
      "type": "http",
      "url": "https://<org>.mcp-s.com/mcp/mcp/google-datastream"
    }
  }
}

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "willow-google-datastream": {
      "type": "http",
      "url": "https://<org>.mcp-s.com/mcp/mcp/google-datastream"
    }
  }
}

Claude Code

CLI

claude mcp add willow-google-datastream --transport http https://<org>.mcp-s.com/mcp/mcp/google-datastream

n8n

HTTP Request Node

{
  "url": "https://<org>.mcp-s.com/mcp/mcp/google-datastream",
  "method": "POST"
}

Or click "Install with Willow" above to set up automatically with SSO and RBAC preconfigured.

Enterprise Governance for Google Datastream

Willow adds the layer Google Datastream and every other SaaS doesn't ship out of the box: every call runs behind SSO (Okta, Azure AD), enforces RBAC and least-privilege at runtime, writes to full audit logs, and detects shadow AI usage across your stack. One MCP gateway. Any agent. Every tool.

Google Datastream MCP Server FAQ

What is the Google Datastream MCP server?

The Google Datastream MCP server is a Model Context Protocol implementation that lets AI agents like Claude, Cursor, and ChatGPT read and write Google Datastream data through a standardized interface. Willow hosts and governs this server so enterprises can roll it out without a security review backlog.

How is Willow's Google Datastream MCP server different from the official one?

The official Google Datastream MCP server is scoped to a single user's account and does not include enterprise governance. Willow's version adds SSO, RBAC, audit logging, shadow AI detection, and centralized control over which actions agents can take across the entire org.

Which AI clients work with the Google Datastream MCP server?

Claude Desktop, Claude Code, Cursor, ChatGPT, VS Code with MCP support, n8n, and any custom agent built with OpenAI Agents SDK, LangChain, Vercel AI SDK, or Anthropic SDK.

Is the Google Datastream MCP server secure? How does Willow handle authentication?

Every call runs behind your existing SSO (Okta, Azure AD). Per-user OAuth scopes the agent to exactly what that user can do in Google Datastream, nothing more. No credentials reach the LLM. Every action writes to an audit trail.

Can I limit which Google Datastream actions agents can take?

Yes. Willow lets you scope agents to specific actions, specific projects, or specific environments. Toggle actions on or off in the dashboard, or enforce policy via infrastructure-as-code through GitHub.

How do I detect shadow Google Datastream MCP servers in my org?

Willow's browser extension and discovery service surface unmanaged MCP servers, skills, and AI agents across the org. If a developer installed an unapproved Google Datastream MCP locally, you'll see it.

What does the Google Datastream MCP server cost?

Pricing depends on org size and deployment model (SaaS, dedicated cloud, self-host). See withwillow.ai/pricing or contact sales for a quote.

How do I install the Google Datastream MCP server with Willow?

Install via the Willow Connect Panel in one click, or paste the JSON snippet above into your Claude Desktop, Cursor, or Claude Code config. SSO and RBAC inherit from your existing Willow setup.