Hosting

Google-managed remote

Transport

Streamable HTTP

Endpoint

https://firebasedataconnect.googleapis.com/mcp

Authentication

Google Cloud authentication: OAuth 2.0 using Application Default Credentials (ADC) in supported Google clients, or a client OAuth ID/secret or bearer token in compatible third-party clients. The principal needs mcp.tools.call plus the underlying product permissions; API key authentication is only available for services that explicitly support it.

Requirements

• A Google Cloud project and access to the target product/resource.
• Enable this MCP service and its underlying Google Cloud API as required by the product guide.
• An MCP client that supports Streamable HTTP.
• An identity with the MCP Tool User role (roles/mcp.toolUser) or equivalent mcp.tools.call permission, plus permissions for the underlying product operations.

Setup steps

1. Choose the correct global or regional endpoint for your data location; this catalog lists the documented endpoint.
2. In the Google Cloud project, enable the MCP service and the underlying product API if the product guide requires it.
3. Authenticate the client with Google Cloud ADC (simplest with Antigravity/Gemini CLI) or configure OAuth 2.0 credentials in a compatible client.
4. Grant the connecting identity roles/mcp.toolUser and only the product IAM roles needed for the intended operations.
5. Add firebasedataconnect.googleapis.com to the client as a Streamable HTTP MCP server and complete sign-in.
6. Refresh the client tool list and check that the tools match the product reference; availability may depend on permissions and selected toolset.

Eleven tools manage Firebase SQL Connect services and execute/generate GraphQL operations. execute_graphql can change database-backed application data; use execute_graphql_read for read-only requests and review generated queries/schema before execution. Preview and IAM apply.

• update_service

  Updates the parameters of a single SQL Connect Service instance. Allows modifying service metadata, labels, and other configurations of the managed backend component. When to use it: Use this tool to modify configurations of an existing Service instance (such as display name, labels, or annotations). How to use it: Call update_service with projectId , location , serviceId to identify the service, and provide the fields you want to update (e.g. displayName , labels , annotations ). Provide an updateMask specifying which fields to overwrite. This is an asynchronous operation and returns a long-running operation. You MUST use the get_operation tool with the returned operation name to poll for completion. JSON Example: { "projectId": "my-project", "location": "us-central1", "serviceId": "my-service", "displayName": "Production Service", "labels": { "env": "production" }, "updateMask": "displayName,labels" }

  01
• delete_service

  Deletes a single SQL Connect Service instance. Deleting a service instance will remove the managed backend component, including its associated schemas and connectors. It does NOT delete the underlying databases. When to use it: Use this tool to permanently remove a Service instance. How to use it: Call delete_service with projectId , location , serviceId to identify the service. Set force to true if you want to delete the service and all its child resources (schemas, connectors). If force is false or unset, the deletion will fail if child resources exist. This is an asynchronous operation and returns a long-running operation. You MUST use the get_operation tool with the returned operation name to poll for completion. JSON Example: { "projectId": "my-project", "location": "us-central1", "serviceId": "my-service", "force": true }

  02
• get_service

  Gets details of a single SQL Connect Service instance. Retrieves the configuration and status of the managed backend component. When to use it: Use this tool to retrieve the current state, configuration, and status of a specific Service instance. How to use it: Call get_service with projectId , location , and serviceId . JSON Example: { "projectId": "my-project", "location": "us-central1", "serviceId": "my-service" }

  03
• list_services

  Lists SQL Connect Service instances in a given project and location. When to use it: Use this tool to retrieve a list of SQL Connect Service instances within a specific project. How to use it: Call list_services with projectId and an optional location . If location is omitted or set to "-", it lists services across all locations. Use list_locations to see all supported locations. Supports pagination with pageSize and pageToken . By not providing pageSize , it returns as many services as the server can pack into a single response. But you must still use pageToken to get the next page of results. Supports filtering with filter and ordering with orderBy . The returned service name contains the project, location, and service name, which can be used to call other tools. Ex. with projectId=my-project , location=us-central1 , and serviceId=my-service , the returned service name would be projects/my-project/locations/us-central1/services/my-service JSON Example: { "projectId": "my-project", "pageSize": 10 }

  04
• list_locations

  Lists information about the supported locations. When to use it: Use this tool to discover which Google Cloud regions are supported by Firebase SQL Connect for your project. How to use it: Call list_locations with the name parameter set to the project resource name (e.g., projects/my-project ). Supports pagination with pageSize and pageToken . By not providing pageSize , it returns as many locations as the server can pack into a single response. But you must still use pageToken to get the next page of locations. Supports filtering with filter . JSON Example: { "name": "projects/my-project", "pageSize": 10 }

  05
• get_operation

  Gets the latest state of a long-running operation. When to use it: Use this tool to poll the status of an asynchronous task (like updating or deleting a service) until it completes. How to use it: Call get_operation with the resource name of the operation. Check the done field in the response. If true, the operation is complete. JSON Example: { "name": "projects/my-project/locations/us-central1/operations/my-operation" }

  06
• execute_graphql

  Executes any GraphQL query or mutation against a Firebase SQL Connect Service instance. Grants full read and write access to the connected data sources. When to use it: Use this tool to execute arbitrary GraphQL queries or mutations against your SQL Connect schema (e.g. inserting, updating, deleting data, or complex reads). How to use it: Call execute_graphql with projectId , location , serviceId to identify the service, and provide the GraphQL query string. Optionally provide variables , operationName , and extensions . JSON Example: { "projectId": "my-project", "location": "us-central1", "serviceId": "my-service", "query": "mutation CreateUser($name: String!) { createUser(data: {name: $name}) { id } }", "variables": { "name": "Alice" } }

  07
• execute_graphql_read

  Executes a read-only GraphQL query against a Firebase SQL Connect Service instance. Grants read access to the connected data sources. Identical to execute_graphql except it only accepts read-only queries. When to use it: Use this tool to execute read-only GraphQL queries (fetching records, filtering, listing data). How to use it: Call execute_graphql_read with projectId , location , serviceId to identify the service, and provide the GraphQL query string. Optionally provide variables , operationName , and extensions . JSON Example: { "projectId": "my-project", "location": "us-central1", "serviceId": "my-service", "query": "query GetUser($id: UUID!) { user(id: $id) { name } }", "variables": { "id": "123e4567-e89b-12d3-a456-426614174000" } }

  08
• generate_query

  Generates a GraphQL query based on a natural language prompt and an existing deployed service schema. When to use it: Use this tool to generate GraphQL queries against an existing deployed Firebase Data Connect service schema. How to use it: Call generate_query with projectId , location , serviceId , and prompt . JSON Example: { "projectId": "my-project", "location": "us-central1", "serviceId": "my-service", "prompt": "List all movies in the Action genre" }

  09
• generate_query_from_schema

  Generates a GraphQL query based on a natural language prompt and a user-provided local GraphQL schema. When to use it: Use this tool to generate GraphQL queries using a local GraphQL schema string without requiring a deployed service. How to use it: Call generate_query_from_schema with projectId , location , schema (GraphQL SDL content string), and prompt . Use list_locations to find a valid location for location (any location works; choosing a closer region reduces latency). JSON Example: { "projectId": "my-project", "location": "us-central1", "schema": "type Movie @table { title: String! genre: String }", "prompt": "List all movies in the Action genre" }

  10
• generate_schema

  Generates a GraphQL schema based on a natural language prompt or data description. When to use it: Use this tool to scaffold new GraphQL schema types and tables using natural language prompts. How to use it: Call generate_schema with projectId , location , and prompt . Use list_locations to find a valid location for location (any location works; choosing a closer region reduces latency). JSON Example: { "projectId": "my-project", "location": "us-central1", "prompt": "Create a blog schema with Users, Posts, and Comments" }

  11

• Google marks this service Preview in its supported-products catalog.

• official tool reference

  Product-specific Google MCP reference publishes 11 exact tool identifiers and descriptions in its tools reference.

• official setup guide

  Google Cloud describes remote MCP client setup, Streamable HTTP transport, supported authentication options, and ADC setup.

• official authentication guide

  Google documents supported identity types and authorization requirements for Google Cloud MCP calls.

• official source

  Official Google Cloud primary MCP reference/setup checked 2026-10-28.

• official source

  Official Google Cloud primary MCP reference/setup checked 2026-10-28.

Documentation checked 2026-10-28. Connection has not been runtime tested.