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ariesanhthu

VNStock MCP Server

by ariesanhthu

get_all_industries

Retrieve all industry symbols from the Vietnam stock market in JSON or DataFrame format for market analysis and data processing.

Instructions

Get all symbols from stock market
Args:
    output_format: Literal['json', 'dataframe'] = 'json'
Returns:
    pd.DataFrame or json

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
output_formatNojson

Implementation Reference

  • Handler function decorated with @server.tool() for MCP registration. Implements the core logic to fetch all industries using VCIListing.industries_icb() and format output as JSON or pandas DataFrame based on the input parameter.
    @server.tool()
    def get_all_industries(output_format: Literal["json", "dataframe"] = "json"):
        """
        Get all symbols from stock market
        Args:
            output_format: Literal['json', 'dataframe'] = 'json'
        Returns:
            pd.DataFrame or json
        """
        listing = VCIListing()
        df = listing.industries_icb()
        if output_format == "json":
            return df.to_json(orient="records", force_ascii=False)
        else:
            return df
  • The @server.tool() decorator registers get_all_industries as an MCP tool.
    @server.tool()
  • Type hints define the input schema: optional output_format parameter with Literal['json', 'dataframe'] defaulting to 'json'. FastMCP infers tool schema from this and docstring.
    def get_all_industries(output_format: Literal["json", "dataframe"] = "json"):
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral information. It mentions the return type options but doesn't disclose whether this is a read-only operation, if there are rate limits, authentication requirements, or what 'all symbols' actually means in scope. The description is insufficient for a tool with no annotation coverage.

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

Conciseness3/5

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

The description is brief but poorly structured - it starts with an unclear purpose statement, then provides parameter documentation. While concise, the front-loading is ineffective due to the vague opening. The information about returns is useful but could be better integrated.

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?

For a tool with no annotations, no output schema, and unclear purpose relative to siblings, the description is inadequate. It covers the parameter but fails to explain what the tool actually returns (what 'symbols' means, what data fields are included, how industries relate to symbols) or when to use it versus similar tools.

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

Parameters4/5

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

The description provides clear parameter information for the single parameter 'output_format', explaining the two possible values and their return types. With 0% schema description coverage and only one parameter, this adequately compensates for the schema gap, though it doesn't explain why one format might be preferred over the other.

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

Purpose2/5

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

The description states 'Get all symbols from stock market' which is a tautology of the tool name 'get_all_industries' - it doesn't clarify what 'industries' means or how it relates to symbols. It fails to distinguish this tool from sibling tools like 'get_all_symbols' or 'get_all_symbols_by_industry', leaving the purpose ambiguous.

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

Usage Guidelines1/5

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

No guidance is provided on when to use this tool versus alternatives like 'get_all_symbols' or 'get_all_symbols_by_industry'. The description offers no context about appropriate use cases or exclusions, making it impossible for an agent to make informed decisions.

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

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