What the Data for This Category Looks Like
Baijiu market data is sourced from public market interfaces of domestic securities exchanges and public monitoring data for the food and beverage sector. The update schedule is: real-time trading data updates every 5 seconds during trading days, and complete daily yield statistics are generated after market close each day. Document structures are structured tables or JSON format, including the following fields: 证券代码, 证券简称, 所属板块, 开盘价（元）, 收盘价（元）, 当日价格变动幅度, 累计收益率, 成交量（股）, 成交额（元）, 数据更新时间戳. Units are as follows: price-related fields use yuan, trading volume uses shares, and transaction amount uses yuan.
Constraints Imposed on Tool Calling and Plugins by These Characteristics
Baijiu market data characteristics impose multiple constraints on the tool calling and plugins link. First, public market data interfaces require valid authentication keys, so plugin configurations must bind the corresponding service provider’s API key. Second, real-time data updates every 5 seconds. Tool calling trigger frequency must not exceed this interval, otherwise duplicate unupdated data will be returned. Third, structured data includes fixed fields. Tools must support filtering by parameters such as sector, security code, to avoid returning irrelevant data. Fourth, data transmission volume increases as the scope of covered sectors expands. Field filtering parameters must be configured to optimize calling efficiency.
How to Configure the Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
mcp_server_url | http://localhost:8081/mcp/aisignal | Corresponds to the official deployment address of the baijiu market MCP plugin; the default port for new versions is 8081 |
mcp_api_key | sk-xxxxxxxxxxxxxxxx | Binds the authentication key from a third-party market data service provider, used to obtain valid baijiu sector data |
tool_cache_ttl | 5 seconds | Matches the 5-second update interval of A-share real-time market data, ensuring the latest data is returned |
tool_request_timeout | 10 seconds | Adapts to the typical response latency of A-share market interfaces, preventing call failures due to network delays |
required_tool_fields | Security Code, Security Abbreviation, Closing Price, Daily Price Change Range, Transaction Volume | Filters out irrelevant fields, reduces data transmission volume and focuses on core metrics |
trigger_frequency_limit | 1 times/6 seconds | Matches the call limit of the A-share market interface, avoiding triggering rate-limiting mechanisms |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Issue: After upgrading
fastgpt-mcp-serverto v0.12.0, aport already in useerror is returned on startup. Cause: The default port was adjusted from 8080 to 8081 in the new version, and port conflicts occur because the port parameter in the configuration file was not modified. - Issue: After calling the baijiu market MCP tool, the model context is cleared, and multi-turn conversations cannot continue. Cause: The
context_keepparameter was not configured correctly for the tool call response, causing FastGPT to reset the current session context. - Issue: When calling the baijiu market tool in a workflow, only data for a single stock can be obtained, and filtering by sector or multiple stocks is not possible. Cause: The
filter_paramsparameter was not configured in the workflow node, and no filtering conditions were specified, causing the tool to return only the default single entry of data.
How to Verify Successful Configuration
- Start
fastgpt-mcp-serverand check the console output to confirm there are no connection errors or port conflict error messages. - Use the tool testing page in FastGPT to call the baijiu market tool, input sector filtering parameters, and check if the returned results include the preset core fields.
- Add a tool call node to the workflow, configure multi-parameter filtering conditions, run the workflow, and check if the returned results meet the filtering requirements.
- Call the tool multiple times consecutively with an interval of no more than 6 seconds, and confirm that no rate-limiting related error codes are returned.
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.