1. use_case: - Create a summary report in the specified workspace and table in Zoho Analytics. - Use this to generate grouped aggregate reports, ideal for quick summaries with group-by and aggregate logic. - Creates a summary table that groups data by specified columns and applies aggregate funct...
AI agents use create_summary_report to create or update resources in Zoho Analytics — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Zoho Analytics environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
orgId | string | — | |
filters | array | — | |
tableName | string | Yes | |
reportName | string | Yes | |
workspaceId | string | Yes | |
summaryDetails | object | Yes |
Parameters from the server's own tool schema.
The tool performs write operations by creating new report objects (summary report) and summary tables within Zoho Analytics. This is a reversible modification of the data structure/content—reports and tables can be deleted or modified later. It does not execute arbitrary code, delete irreversibly, move money, or merely read data.
From the tool's definition Tool creates a summary report and creates a summary table that groups data by specified columns and applies aggregate functions. This modifies the workspace by adding new report objects and tables.
Risk signalsHigh parameter count (20 properties)
Attacks that exploit this kind of access
1. use_case: - Create a summary report in the specified workspace and table in Zoho Analytics. - Use this to generate grouped aggregate reports, ideal for quick summaries with group-by and aggregate logic. - Creates a summary table that groups data by specified columns and applies aggregate functions. 2. important_notes: - Do NOT use "actual" operation for numeric columns in aggregate. Use "sum" instead. - You can use lookup columns from other tables if relationships are already defined. 3. arguments: - workspace_id (str): The ID of the workspace to create the Summary report in. - table_name (str): The name of the base table for the summary report. - report_name (str): The name for the Summary to be created. - summary_details (dict): Contains: - group_by (list[dict]): Each dict must have: - columnName (str) - tableName (str) - operation (str): Below are the valid operation types based on datatypes Date: year, quarterYear, monthYear, weekYear, fullDate, dateTime, range, quarter, month, week, weekDay, day, hour, count, distinctCount String: actual, count, distinctCount Number: measure, dimension, sum, average, min, max, count, distinctCount - aggregate (list[dict]): Each dict must have: - columnName (str) - operation (str): sum, average, count, min, max, etc. - tableName (str): Need to be provided if the column belongs to another table with which a lookup is defined. - filters (list[dict] | None): Optional filters. See <filters_args> in create_chart tool. - org_id (str | None): The ID of the organization to which the workspace belongs to. If not provided, it defaults to the organization ID from the configuration. 3.1. filter_args: - tableName (str): The name of the table containing the column to filter. - columnName (str): The name of the column to filter. - operation (str): Specifies the function applied to the specified column used in the filter. The accepted functions differ based on the data type of the column. Date: actual, seasonal, relative String: actual, count, distinctCount Number: measure, dimension, sum, average, min, max, count, distinctCount - filterType (str): The type of filter to apply. Accepted values: individualValues, range, ranking, rankingPct, dateRange, year, quarterYear, monthYear, weekYear, quarter, month, week, weekDay, day, hour, dateTime - values (list): The values to filter on. Example: - For individualValues: "value1", "value2" - For range: "10 to 20", "50 and above" - For ranking: "top 10", "bottom 5" - exclude (bool): Whether to exclude or include the filtered values. Default is False. 4.returns: - str: Chart creation status or error message. It is categorised as a Write tool in the Zoho Analytics MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
create_summary_report accepts 6 parameters: orgId, filters, tableName, reportName, workspaceId, summaryDetails. Required: tableName, reportName, workspaceId, summaryDetails. The full parameter table on this page comes from the server's own tool schema.
Register the Zoho Analytics MCP server in PolicyLayer and add a rule for create_summary_report: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Zoho Analytics. Nothing to install.
create_summary_report is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the create_summary_report rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for create_summary_report. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
create_summary_report is provided by the Zoho Analytics MCP server (zoho-analytics-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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