Skip to main content
Glama
MaoBui2907

VNStock MCP Server

by MaoBui2907

get_company_dividends

Retrieve dividend history for any Vietnam stock symbol. Returns dividend payments data in JSON, DataFrame, or AI-optimized format.

Instructions

Get company dividends from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes
output_formatNotoon
Behavior2/5

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

No annotations provided. Description does not disclose non-obvious behaviors such as rate limits, authentication requirements, or whether the operation is read-only. It mentions that 'toon' format is optimized for AI, which is a minor behavioral hint.

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 short and front-loaded with the main purpose. The docstring format for Args and Returns is clear, though slightly verbose. Every sentence adds value.

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

Completeness3/5

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

With no annotations or output schema, the description covers the basic purpose and parameters. However, it lacks details about the return structure (e.g., fields of the DataFrame), any filtering capabilities, or pagination. It is minimally complete.

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?

Schema coverage is 0%, so description must add value. It explains the default and meaning of output_format ('toon is optimized for AI') and lists the enum options. symbol is not elaborated, but overall it provides meaningful context beyond the raw schema.

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 'Get company dividends from stock market' clearly states the action and resource. It distinguishes from sibling tools like get_income_statements or get_company_events, but does not explicitly differentiate itself.

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?

No guidance on when to use this tool versus alternatives (e.g., get_company_events for other financial data). No preconditions or exclusions mentioned.

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/MaoBui2907/vnstock-mcp-server'

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