What the data for this category looks like
Data for advertising and marketing financing daily reports mainly comes from internal placement ledgers of advertising agencies, real-time placement reports from partner media platforms, and aggregated data from third-party marketing data monitoring institutions. Data is updated on a daily schedule: full daily data collection is completed each evening, and the official daily report is released the next day. Documents use structured tables as the main structure. Core fields include placement channel type, placement budget execution amount, impressions, clicks, customer acquisition cost per customer, and converted order count. Corresponding units are channel category, ten thousand yuan, thousand impressions, times, yuan/customer, and order.
What constraints these characteristics impose on tool calling and plugins
Data for advertising and marketing financing daily reports has multiple sources and rich field dimensions. Tool calling must support parameterized filtering by dimensions such as channel and time period, to avoid returning redundant full-volume data. Data updates once daily. Tool trigger timing should not be too frequent, and must adapt to the T+1 update cycle. This prevents pulling temporary data that has not completed collection. There is interface response delay when pulling data across media platforms. The timeout threshold for tool calling must adapt to the time required to merge multi-source data. Fields include numeric types with different units. Tool return results must clearly mark units, to avoid the model confusing data meanings. At the same time, format differences across multi-source data require plugins to include built-in standardization conversion logic, to unify field names and units.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale for This Value |
|---|---|---|
mcp_tool_timeout | 300 seconds | Average cross-platform data pulling time for advertising and marketing data ranges from 2 to 5 minutes, with reasonable buffer space reserved |
mcp_batch_request_limit | 5 | A single advertising and marketing financing daily report usually involves no more than 5 types of placement channels, to avoid request overload |
workflow_auto_trigger_cron | 0 22 * * * | Adapts to the schedule where most media platforms complete data collection by 22:00 daily |
parameter_fill_prompt | Please specify query channels and statistical time range | Clearly guides users to supplement dimensional parameters required for tool calling |
response_normalization | Auto-convert to unified units | Resolves the issue of inconsistent units across multi-source data, avoiding model parsing errors |
external_api_callback_url | Fill in your web app's receiving address | Supports fast integration of FastGPT applications with self-owned web applications via callback |
The parameter values provided on this page are all common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Mistakes
- The symptom is slowed model responses after calling MCP tools. The cause is failure to set a reasonable timeout period, with context resources occupied while the tool waits for a response.
- The symptom is empty field returns when the workflow calls MCP. The cause is lack of configured parameter verification rules, and failure to guide users to supplement necessary parameters such as placement channels and time periods.
- The symptom is context interruption each time an MCP tool is called. The cause is an overly small context window configuration, with previous parameter requests and associated information not retained.
How to Confirm the Configuration Is Complete
- Manually trigger the workflow, enter test placement channels and time periods, check if the tool returns financing daily report data for the corresponding dimensions.
- View tool call logs, confirm there are no
ETIMEDOUTtimeout errors or400 Bad Requestparameter missing errors. - Check that the field units of returned data are unified, and confirm that the standardization conversion logic is effective.
- Configure a scheduled trigger task, check the automatically generated daily report results the next day to see if they meet the daily update cycle requirements.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.