What Data for This Category Looks Like
Engineering consulting yield rate and market daily report data comes from three main sources: official regional cost indices released by housing and urban-rural development department official cost platforms, project survey datasets from industry consulting associations, and internal financial ledger data provided by project clients.
Data update cadences vary: daily material and equipment market unit prices are updated each day. Aggregated survey data for project benchmark yield rates is updated weekly. Some customized specialized yield rate data is released with a 2-business-day delay.
Documents use structured tables as their core format. Each daily report includes a report period and submitting organization header, plus entries categorized by engineering type. Each row contains fields such as project category, current day market unit price, benchmark yield value for the corresponding period, and dynamic adjustment coefficient. Units include common engineering industry units such as yuan/cubic meter and ten thousand yuan/project.
Constraints Imposed on Tool Calling and Plugins
First, multi-source data integration requires plugins to support cross-platform aggregation configuration. Plugins must distinguish permission check rules for official public data and internal private data.
Second, differing data update frequencies require scheduled tasks for tool calling to support segmented periodic configuration. This avoids repeatedly pulling expired data or missing updated content.
Third, the structured table document format requires plugins to have precise table parsing and field mapping capabilities. Plugins must adapt to engineering consulting-specific non-universal fields such as project codes and dynamic adjustment coefficients.
Fourth, delayed data releases require adding data expiration filtering logic during tool calls. This prevents returning old data older than 2 business days.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
tool_call_timeout | 300 seconds | Bulk data pulling from engineering consulting data sources typically takes under 200 seconds, so this sets a reasonable buffer |
multi_source_merge_strategy | Deduplicate and merge by report date | Report dates from different data sources may differ by 1-2 days, so aggregate valid data using report date as the benchmark |
data_refresh_interval | 86400 seconds | Market data updates daily. Yield rate aggregated data can have its cycle adjusted separately via scheduled task sub-items |
field_mapping_template | Map using engineering consulting industry standard fields | Data includes unique fields such as project codes and dynamic adjustment coefficients, so it needs to match industry general mapping rules |
permission_check_enabled | Enabled | Differentiate access permissions for public data sources and internal private data to ensure data security |
sse_connection_timeout | 60 seconds | MCP service connection establishment and data pulling processes typically take under 45 seconds, so this sets a reasonable buffer |
The parameter values provided on this page are all conventional recommendations used as starting points for configuration. Actual values are affected by material form, 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 Configuration Mistakes
- Issue: Returns
504 Gateway Timeouterror when calling the tool. Cause: Did not configuretool_call_timeoutto a value greater than 300 seconds, causing timeout interruption during bulk pulling of engineering consulting data. - Issue: Yield rate fields returned by tool calls are empty. Cause: Did not use the engineering consulting industry standard
field_mapping_template, causing unique fields to fail to map correctly to the target format. - Issue: Unable to establish an SSE connection when calling the MCP service with version 4.8. Cause: The default SSE connection timeout threshold for version 4.8 is set to 30 seconds, and was not adjusted to match the actual duration required for pulling engineering consulting data.
How to Verify Proper Configuration
- Manually trigger a tool call, check if the returned structured data includes engineering consulting-specific fields such as project codes and dynamic adjustment coefficients, and that field matching conforms to the preset mapping rules.
- Review tool call logs to confirm that the multi-source data aggregation logic executes normally, with no duplicate or missing report date entries.
- Verify the MCP service connection status, check whether the latest data from the corresponding data sources can be pulled normally, and that the connection duration conforms to the configured
sse_connection_timeoutthreshold. - Test the tool call termination logic, confirm that when preset termination conditions are triggered, the tool call stops normally and returns currently acquired valid data.
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.