MCP Reference: bigquerymigration.googleapis.com

BigQuery Migration MCP server provides tools to work with BigQuery Migration Services, such as SQL translation.

A Model Context Protocol (MCP) server acts as a proxy between an external service that provides context, data, or capabilities to a Large Language Model (LLM) or AI application. MCP servers connect AI applications to external systems such as databases and web services, translating their responses into a format that the AI application can understand.

Server Setup

You must enable MCP servers and set up authentication before use. For more information about using Google and Google Cloud remote MCP servers, see Google Cloud MCP servers overview.

Server Endpoints

An MCP service endpoint is the network address and communication interface (usually a URL) of the MCP server that an AI application (the Host for the MCP client) uses to establish a secure, standardized connection. It is the point of contact for the LLM to request context, call a tool, or access a resource. Google MCP endpoints can be global or regional.

The BigQuery Migration API MCP server has the following global MCP endpoint:

  • https://bigquerymigration.googleapis.com/mcp

MCP Tools

An MCP tool is a function or executable capability that an MCP server exposes to a LLM or AI application to perform an action in the real world.

Tools

The bigquerymigration.googleapis.com MCP server has the following tools:

MCP Tools
translate_query Translates a single query into BigQuery SQL syntax. The translation runs asynchronously: use the get_translation tool with the returned translation ID to poll its state until it is SUCCEEDED or FAILED. Wait at least 2 seconds before rechecking the state.
get_translation Gets the SQL translation for a given translation ID. If the state is not yet SUCCEEDED or FAILED, wait at least 2 seconds before rechecking the state.
explain_translation Explains the SQL translation for a given translation ID.
generate_ddl_suggestion Suggests Data Definition Language (DDL) statements for an input query. For example, CREATE TABLE or CREATE VIEW. The generated DDL provides schema definitions for tables and views that are used in the query. To get DDL suggestions, call this tool, and then use the fetch_ddl_suggestion tool with the returned suggestion ID to poll its state until it is SUCCEEDED or FAILED and retrieve the DDL. Wait at least 2 seconds before rechecking the state. You can then prepend the retrieved DDL to the original input query and translate it again to improve translation quality.
fetch_ddl_suggestion Fetches DDL suggestion for a given suggestion ID. If the state is not yet SUCCEEDED or FAILED, wait at least 2 seconds before rechecking the state.
translate_batch_queries Translates a batch of SQL queries stored in Google Cloud Storage. The translation runs asynchronously: use the fetch_batch_translation tool with the returned translation ID to poll its state until it is SUCCEEDED or FAILED. Wait at least 10 seconds before rechecking the state.
fetch_batch_translation Retrieves the state and logs of a batch translation workflow. If the state is not yet SUCCEEDED or FAILED, wait at least 10 seconds before rechecking the state.
generate_batch_ddl_suggestion Generates Data Definition Language (DDL) suggestions for a batch translation. The suggestion runs asynchronously: use the fetch_batch_ddl_suggestion tool with the returned suggestion ID to poll its state until it is SUCCEEDED or FAILED. Wait at least 10 seconds before rechecking the state.
fetch_batch_ddl_suggestion Retrieves the state and logs of a batch DDL suggestion workflow. If the state is not yet SUCCEEDED or FAILED, wait at least 10 seconds before rechecking the state.
translate_metadata Translates a metadata zip file into Data Definition Language (DDL) statements and table mappings. The translation runs asynchronously: use the fetch_batch_translation tool with the returned translation ID to poll its state until it is SUCCEEDED or FAILED. Wait at least 10 seconds before rechecking the state.

Get MCP tool specifications

To get the MCP tool specifications for all tools in an MCP server, use the tools/list method. The following example demonstrates how to use curl to list all tools and their specifications currently available within the MCP server.

Curl Request 
curl --location 'https://bigquerymigration.googleapis.com/mcp' \
--header 'content-type: application/json' \
--header 'accept: application/json, text/event-stream' \
--data '{
    "method": "tools/list",
    "jsonrpc": "2.0",
    "id": 1
}'