Skip to main content
Glama
liqiongyu

Xueqiu MCP

by liqiongyu

fund_asset

Retrieve asset allocation data for investment funds to analyze portfolio composition and investment strategies using Xueqiu MCP's financial data services.

Instructions

获取基金资产配置数据

Args:
    fund_code: 基金代码

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fund_codeNoSZ000002

Implementation Reference

  • main.py:453-461 (handler)
    The handler for the fund_asset MCP tool. Registered via @mcp.tool() decorator. Calls pysnowball.ball.fund_asset(fund_code) to fetch fund asset configuration data and processes the result with process_data helper.
    @mcp.tool()
    def fund_asset(fund_code: str="SZ000002") -> dict:
        """获取基金资产配置数据
        
        Args:
            fund_code: 基金代码
        """
        result = ball.fund_asset(fund_code)
        return process_data(result)
  • main.py:34-61 (helper)
    Shared helper function used by fund_asset (and other tools) to process the raw data from pysnowball, including converting timestamps to readable datetime strings.
    def process_data(data, process_config=None):
        """
        通用数据处理函数,可扩展添加各种数据处理操作
        
        Args:
            data: 原始数据
            process_config: 处理配置字典,用于指定要执行的处理操作
                例如: {'convert_timestamps': True, 'other_process': params}
        
        Returns:
            处理后的数据
        """
        if process_config is None:
            # 默认配置
            process_config = {
                'convert_timestamps': True
            }
        
        # 如果开启了时间戳转换
        if process_config.get('convert_timestamps', True):
            data = convert_timestamps(data)
        
        # 在这里可以添加更多的数据处理逻辑
        # 例如:
        # if 'format_numbers' in process_config:
        #     data = format_numbers(data, **process_config['format_numbers'])
        
        return data
  • main.py:14-31 (helper)
    Helper utility called by process_data to recursively convert timestamp fields in the data to human-readable datetime strings.
    def convert_timestamps(data):
        """递归地将数据中的所有 timestamp 转换为 datetime 字符串"""
        if isinstance(data, dict):
            for key, value in list(data.items()):
                if key == 'timestamp' and isinstance(value, (int, float)) and value > 1000000000000:  # 毫秒级时间戳
                    data[key] = datetime.datetime.fromtimestamp(value/1000).strftime('%Y-%m-%d %H:%M:%S')
                elif key == 'timestamp' and isinstance(value, (int, float)) and value > 1000000000:  # 秒级时间戳
                    data[key] = datetime.datetime.fromtimestamp(value).strftime('%Y-%m-%d %H:%M:%S')
                elif key.endswith('_date') and isinstance(value, (int, float)) and value > 1000000000000:  # 毫秒级时间戳
                    data[key] = datetime.datetime.fromtimestamp(value/1000).strftime('%Y-%m-%d %H:%M:%S')
                elif key.endswith('_date') and isinstance(value, (int, float)) and value > 1000000000:  # 秒级时间戳
                    data[key] = datetime.datetime.fromtimestamp(value).strftime('%Y-%m-%d %H:%M:%S')
                elif isinstance(value, (dict, list)):
                    data[key] = convert_timestamps(value)
        elif isinstance(data, list):
            for i, item in enumerate(data):
                data[i] = convert_timestamps(item)
        return data
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. The description only states what data is retrieved without mentioning any behavioral traits like whether this is a read-only operation, what format the data returns in, whether there are rate limits, authentication requirements, or potential side effects. For a data retrieval tool with zero annotation coverage, this is inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise with two sentences - one stating the purpose and one documenting the parameter. It's front-loaded with the main purpose first. However, the English translation 'Args:' followed by Chinese text creates minor structural inconsistency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It doesn't explain what 'asset allocation data' includes, what format it returns, whether there are limitations or prerequisites, or how this differs from other fund tools. For a data retrieval tool in a context with many similar tools, more completeness is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explicitly documents the single parameter 'fund_code' with a brief explanation, but with 0% schema description coverage, the schema provides no parameter documentation. The description adds basic semantic meaning ('基金代码' means fund code), but doesn't provide format requirements, examples beyond the default, or validation rules. This partially compensates for the schema gap but not fully.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as '获取基金资产配置数据' (get fund asset allocation data), which is a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'fund_detail', 'fund_info', or 'fund_achievement', which might also provide fund-related data but with different focus areas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools related to funds (fund_detail, fund_info, fund_achievement, fund_growth, fund_manager, etc.), there's no indication of what makes this tool unique or when it should be preferred over other fund-related tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/liqiongyu/xueqiu_mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server