MCP Toolbox for Databases

// Copyright 2025 Google LLC // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. package bigqueryanalyzecontribution import ( "context" "fmt" "strings" bigqueryapi "cloud.google.com/go/bigquery" yaml "github.com/goccy/go-yaml" "github.com/google/uuid" "github.com/googleapis/genai-toolbox/internal/sources" bigqueryds "github.com/googleapis/genai-toolbox/internal/sources/bigquery" "github.com/googleapis/genai-toolbox/internal/tools" bqutil "github.com/googleapis/genai-toolbox/internal/tools/bigquery/bigquerycommon" "github.com/googleapis/genai-toolbox/internal/util/parameters" bigqueryrestapi "google.golang.org/api/bigquery/v2" "google.golang.org/api/iterator" ) const kind string = "bigquery-analyze-contribution" func init() { if !tools.Register(kind, newConfig) { panic(fmt.Sprintf("tool kind %q already registered", kind)) } } func newConfig(ctx context.Context, name string, decoder *yaml.Decoder) (tools.ToolConfig, error) { actual := Config{Name: name} if err := decoder.DecodeContext(ctx, &actual); err != nil { return nil, err } return actual, nil } type compatibleSource interface { BigQueryClient() *bigqueryapi.Client BigQueryRestService() *bigqueryrestapi.Service BigQueryClientCreator() bigqueryds.BigqueryClientCreator UseClientAuthorization() bool IsDatasetAllowed(projectID, datasetID string) bool BigQueryAllowedDatasets() []string BigQuerySession() bigqueryds.BigQuerySessionProvider } type Config struct { Name string `yaml:"name" validate:"required"` Kind string `yaml:"kind" validate:"required"` Source string `yaml:"source" validate:"required"` Description string `yaml:"description" validate:"required"` AuthRequired []string `yaml:"authRequired"` } // validate interface var _ tools.ToolConfig = Config{} func (cfg Config) ToolConfigKind() string { return kind } func (cfg Config) Initialize(srcs map[string]sources.Source) (tools.Tool, error) { // verify source exists rawS, ok := srcs[cfg.Source] if !ok { return nil, fmt.Errorf("no source named %q configured", cfg.Source) } // verify the source is compatible s, ok := rawS.(compatibleSource) if !ok { return nil, fmt.Errorf("invalid source for %q tool: source %q not compatible", kind, cfg.Source) } allowedDatasets := s.BigQueryAllowedDatasets() inputDataDescription := "The data that contain the test and control data to analyze. Can be a fully qualified BigQuery table ID or a SQL query." if len(allowedDatasets) > 0 { datasetIDs := []string{} for _, ds := range allowedDatasets { datasetIDs = append(datasetIDs, fmt.Sprintf("`%s`", ds)) } inputDataDescription += fmt.Sprintf(" The query or table must only access datasets from the following list: %s.", strings.Join(datasetIDs, ", ")) } inputDataParameter := parameters.NewStringParameter("input_data", inputDataDescription) contributionMetricParameter := parameters.NewStringParameter("contribution_metric", `The name of the column that contains the metric to analyze. Provides the expression to use to calculate the metric you are analyzing. To calculate a summable metric, the expression must be in the form SUM(metric_column_name), where metric_column_name is a numeric data type. To calculate a summable ratio metric, the expression must be in the form SUM(numerator_metric_column_name)/SUM(denominator_metric_column_name), where numerator_metric_column_name and denominator_metric_column_name are numeric data types. To calculate a summable by category metric, the expression must be in the form SUM(metric_sum_column_name)/COUNT(DISTINCT categorical_column_name). The summed column must be a numeric data type. The categorical column must have type BOOL, DATE, DATETIME, TIME, TIMESTAMP, STRING, or INT64.`) isTestColParameter := parameters.NewStringParameter("is_test_col", "The name of the column that identifies whether a row is in the test or control group.") dimensionIDColsParameter := parameters.NewArrayParameterWithRequired("dimension_id_cols", "An array of column names that uniquely identify each dimension.", false, parameters.NewStringParameter("dimension_id_col", "A dimension column name.")) topKInsightsParameter := parameters.NewIntParameterWithDefault("top_k_insights_by_apriori_support", 30, "The number of top insights to return, ranked by apriori support.") pruningMethodParameter := parameters.NewStringParameterWithDefault("pruning_method", "PRUNE_REDUNDANT_INSIGHTS", "The method to use for pruning redundant insights. Can be 'NO_PRUNING' or 'PRUNE_REDUNDANT_INSIGHTS'.") params := parameters.Parameters{ inputDataParameter, contributionMetricParameter, isTestColParameter, dimensionIDColsParameter, topKInsightsParameter, pruningMethodParameter, } mcpManifest := tools.GetMcpManifest(cfg.Name, cfg.Description, cfg.AuthRequired, params, nil) // finish tool setup t := Tool{ Config: cfg, Parameters: params, manifest: tools.Manifest{Description: cfg.Description, Parameters: params.Manifest(), AuthRequired: cfg.AuthRequired}, mcpManifest: mcpManifest, } return t, nil } // validate interface var _ tools.Tool = Tool{} type Tool struct { Config Parameters parameters.Parameters `yaml:"parameters"` manifest tools.Manifest mcpManifest tools.McpManifest } func (t Tool) ToConfig() tools.ToolConfig { return t.Config } // Invoke runs the contribution analysis. func (t Tool) Invoke(ctx context.Context, resourceMgr tools.SourceProvider, params parameters.ParamValues, accessToken tools.AccessToken) (any, error) { source, err := tools.GetCompatibleSource[compatibleSource](resourceMgr, t.Source, t.Name, t.Kind) if err != nil { return nil, err } paramsMap := params.AsMap() inputData, ok := paramsMap["input_data"].(string) if !ok { return nil, fmt.Errorf("unable to cast input_data parameter %s", paramsMap["input_data"]) } bqClient := source.BigQueryClient() restService := source.BigQueryRestService() // Initialize new client if using user OAuth token if source.UseClientAuthorization() { tokenStr, err := accessToken.ParseBearerToken() if err != nil { return nil, fmt.Errorf("error parsing access token: %w", err) } bqClient, restService, err = source.BigQueryClientCreator()(tokenStr, true) if err != nil { return nil, fmt.Errorf("error creating client from OAuth access token: %w", err) } } modelID := fmt.Sprintf("contribution_analysis_model_%s", strings.ReplaceAll(uuid.New().String(), "-", "")) var options []string options = append(options, "MODEL_TYPE = 'CONTRIBUTION_ANALYSIS'") options = append(options, fmt.Sprintf("CONTRIBUTION_METRIC = '%s'", paramsMap["contribution_metric"])) options = append(options, fmt.Sprintf("IS_TEST_COL = '%s'", paramsMap["is_test_col"])) if val, ok := paramsMap["dimension_id_cols"]; ok { if cols, ok := val.([]any); ok { var strCols []string for _, c := range cols { strCols = append(strCols, fmt.Sprintf("'%s'", c)) } options = append(options, fmt.Sprintf("DIMENSION_ID_COLS = [%s]", strings.Join(strCols, ", "))) } else { return nil, fmt.Errorf("unable to cast dimension_id_cols parameter %s", paramsMap["dimension_id_cols"]) } } if val, ok := paramsMap["top_k_insights_by_apriori_support"]; ok { options = append(options, fmt.Sprintf("TOP_K_INSIGHTS_BY_APRIORI_SUPPORT = %v", val)) } if val, ok := paramsMap["pruning_method"].(string); ok { upperVal := strings.ToUpper(val) if upperVal != "NO_PRUNING" && upperVal != "PRUNE_REDUNDANT_INSIGHTS" { return nil, fmt.Errorf("invalid pruning_method: %s", val) } options = append(options, fmt.Sprintf("PRUNING_METHOD = '%s'", upperVal)) } var inputDataSource string trimmedUpperInputData := strings.TrimSpace(strings.ToUpper(inputData)) if strings.HasPrefix(trimmedUpperInputData, "SELECT") || strings.HasPrefix(trimmedUpperInputData, "WITH") { if len(source.BigQueryAllowedDatasets()) > 0 { var connProps []*bigqueryapi.ConnectionProperty session, err := source.BigQuerySession()(ctx) if err != nil { return nil, fmt.Errorf("failed to get BigQuery session: %w", err) } if session != nil { connProps = []*bigqueryapi.ConnectionProperty{ {Key: "session_id", Value: session.ID}, } } dryRunJob, err := bqutil.DryRunQuery(ctx, restService, source.BigQueryClient().Project(), source.BigQueryClient().Location, inputData, nil, connProps) if err != nil { return nil, fmt.Errorf("query validation failed: %w", err) } statementType := dryRunJob.Statistics.Query.StatementType if statementType != "SELECT" { return nil, fmt.Errorf("the 'input_data' parameter only supports a table ID or a SELECT query. The provided query has statement type '%s'", statementType) } queryStats := dryRunJob.Statistics.Query if queryStats != nil { for _, tableRef := range queryStats.ReferencedTables { if !source.IsDatasetAllowed(tableRef.ProjectId, tableRef.DatasetId) { return nil, fmt.Errorf("query in input_data accesses dataset '%s.%s', which is not in the allowed list", tableRef.ProjectId, tableRef.DatasetId) } } } else { return nil, fmt.Errorf("could not analyze query in input_data to validate against allowed datasets") } } inputDataSource = fmt.Sprintf("(%s)", inputData) } else { if len(source.BigQueryAllowedDatasets()) > 0 { parts := strings.Split(inputData, ".") var projectID, datasetID string switch len(parts) { case 3: // project.dataset.table projectID, datasetID = parts[0], parts[1] case 2: // dataset.table projectID, datasetID = source.BigQueryClient().Project(), parts[0] default: return nil, fmt.Errorf("invalid table ID format for 'input_data': %q. Expected 'dataset.table' or 'project.dataset.table'", inputData) } if !source.IsDatasetAllowed(projectID, datasetID) { return nil, fmt.Errorf("access to dataset '%s.%s' (from table '%s') is not allowed", projectID, datasetID, inputData) } } inputDataSource = fmt.Sprintf("SELECT * FROM `%s`", inputData) } // Use temp model to skip the clean up at the end. To use TEMP MODEL, queries have to be // in the same BigQuery session. createModelSQL := fmt.Sprintf("CREATE TEMP MODEL %s OPTIONS(%s) AS %s", modelID, strings.Join(options, ", "), inputDataSource, ) createModelQuery := bqClient.Query(createModelSQL) // Get session from provider if in protected mode. // Otherwise, a new session will be created by the first query. session, err := source.BigQuerySession()(ctx) if err != nil { return nil, fmt.Errorf("failed to get BigQuery session: %w", err) } if session != nil { createModelQuery.ConnectionProperties = []*bigqueryapi.ConnectionProperty{ {Key: "session_id", Value: session.ID}, } } else { // If not in protected mode, create a session for this invocation. createModelQuery.CreateSession = true } createModelJob, err := createModelQuery.Run(ctx) if err != nil { return nil, fmt.Errorf("failed to start create model job: %w", err) } status, err := createModelJob.Wait(ctx) if err != nil { return nil, fmt.Errorf("failed to wait for create model job: %w", err) } if err := status.Err(); err != nil { return nil, fmt.Errorf("create model job failed: %w", err) } // Determine the session ID to use for subsequent queries. // It's either from the pre-existing session (protected mode) or the one just created. var sessionID string if session != nil { sessionID = session.ID } else if status.Statistics != nil && status.Statistics.SessionInfo != nil { sessionID = status.Statistics.SessionInfo.SessionID } else { return nil, fmt.Errorf("failed to get or create a BigQuery session ID") } getInsightsSQL := fmt.Sprintf("SELECT * FROM ML.GET_INSIGHTS(MODEL %s)", modelID) getInsightsQuery := bqClient.Query(getInsightsSQL) getInsightsQuery.ConnectionProperties = []*bigqueryapi.ConnectionProperty{{Key: "session_id", Value: sessionID}} job, err := getInsightsQuery.Run(ctx) if err != nil { return nil, fmt.Errorf("failed to execute get insights query: %w", err) } it, err := job.Read(ctx) if err != nil { return nil, fmt.Errorf("unable to read query results: %w", err) } var out []any for { var row map[string]bigqueryapi.Value err := it.Next(&row) if err == iterator.Done { break } if err != nil { return nil, fmt.Errorf("failed to iterate through query results: %w", err) } vMap := make(map[string]any) for key, value := range row { vMap[key] = value } out = append(out, vMap) } if len(out) > 0 { return out, nil } // This handles the standard case for a SELECT query that successfully // executes but returns zero rows. return "The query returned 0 rows.", nil } func (t Tool) ParseParams(data map[string]any, claims map[string]map[string]any) (parameters.ParamValues, error) { return parameters.ParseParams(t.Parameters, data, claims) } func (t Tool) Manifest() tools.Manifest { return t.manifest } func (t Tool) McpManifest() tools.McpManifest { return t.mcpManifest } func (t Tool) Authorized(verifiedAuthServices []string) bool { return tools.IsAuthorized(t.AuthRequired, verifiedAuthServices) } func (t Tool) RequiresClientAuthorization(resourceMgr tools.SourceProvider) (bool, error) { source, err := tools.GetCompatibleSource[compatibleSource](resourceMgr, t.Source, t.Name, t.Kind) if err != nil { return false, err } return source.UseClientAuthorization(), nil } func (t Tool) GetAuthTokenHeaderName(resourceMgr tools.SourceProvider) (string, error) { return "Authorization", nil }