What the data for this category looks like
Financial report data for professional chain stores primarily comes from store POS systems, supply chain management systems, and headquarters financial accounting systems. Core data update cycles follow monthly, quarterly, and annual schedules. Some individual store operational data can be updated daily. Document structures typically include modules such as headquarters revenue summaries, regional branch operational data, per-store per-square-meter efficiency, supply chain cost proportion, inventory turnover status, and more. Fields include average daily sales per store (unit: yuan), total number of stores, per-square-meter per-day efficiency (yuan/square meter/day), inventory turnover rate (times/quarter), and other metrics. Some documents also include separate operational detail tables for each store.
What constraints do these characteristics impose on tool calling and plugins?
Dispersed data sources across multiple stores mean financial report data must be retrieved via batch pulling tools, which places clear requirements on the tool's concurrent calling capabilities. Data update cycles vary across different modules, so tool trigger timing must be configured specifically to avoid pulling expired data. Fields include clear unit identifiers. Tools must automatically recognize and verify unit formats during calls to prevent unit confusion in analysis results. Documents contain a large number of detail tables, so tools must support chunked parsing to avoid context overflow caused by overly long single segments. Additionally, some store data has been desensitized. Tools must automatically filter sensitive fields during calls to ensure data compliance.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Professional chain store financial reports often include multi-store detail data, resulting in large file sizes and parsing times that far exceed those of general documents |
maxContext | 8000–12000 characters | Financial report content includes cross-region associated data, so sufficient context must be retained to ensure coherent tool calling logic |
Recall Count | Top 6 entries | Financial reports have numerous closely related fields, so enough relevant segments must be recalled to support tool parameter matching |
Similarity Threshold | 0.75–0.85 | Avoid low-relevance scattered store data interfering with the accuracy of tool calls |
MCP Service Address | http://127.0.0.1:8080/mcp | Connect to a locally deployed financial report data pulling service to meet the needs of batch retrieval of multi-store data |
Tool Call Retry Count | 2 retries | Store data interfaces may experience occasional fluctuations; limited retries can reduce call failure rates |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Symptom: Tool calls to the MCP service return a
404 Not Founderror. Cause: The local port of the npx-launched MCP service was not correctly entered in theMCP Service Addressconfiguration item, preventing the platform from connecting to the financial report data pulling interface. - Symptom: Pie charts in generated financial report analysis documents appear as plain text code blocks. Cause: Generic markdown pie chart syntax was used directly, without calling FastGPT's built-in chart generation tool plugin, and the parameter format required by the plugin was not matched.
- Symptom: Per-store per-square-meter efficiency fields are missing from financial report data pulled by the tool. Cause: The list of fields to pull was not specified in the tool call parameters, and the default pulled basic fields do not include efficiency-related data.
How to Confirm Configurations Are Set Correctly
- Access the FastGPT tool management page, check the status of the configured MCP service, and confirm it displays "Connected".
- Manually trigger the financial report data pulling tool, and verify that the returned results include preset fields such as total number of stores, average daily sales per store, and per-square-meter efficiency.
- Submit a test financial report document, call the chart generation tool, and confirm that the generated visual chart can be properly embedded in the generated results.
- View the tool call logs, confirm that the retry count does not exceed the configured
Tool Call Retry Count, and there are no consecutive failure records.
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.