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TWSE MCP Server

TWSE MCP Server

by twjackysu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_real_time_trading_stats

Retrieve real-time 5-second trading statistics from the Taiwan Stock Exchange, including order volumes, transaction counts, and trade values for market analysis.

Instructions

Obtain real-time 5-second trading statistics including order volumes and transaction counts.

Returns the latest 5-second interval trading statistics including:

  • Time: Trading time (HHMMSS format)

  • AccBidOrders: Accumulated bid orders count

  • AccBidVolume: Accumulated bid volume (in shares)

  • AccAskOrders: Accumulated ask orders count

  • AccAskVolume: Accumulated ask volume (in shares)

  • AccTransaction: Accumulated transaction count

  • AccTradeVolume: Accumulated trade volume (in shares)

  • AccTradeValue: Accumulated trade value (in million TWD)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_real_time_trading_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "title": "Result",
-      "type": "string"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "_WrappedResult",
-  "type": "object",
-  "x-fastmcp-wrap-result": true
-}New value: +null
  2. First observed

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the return format and data fields well, but fails to mention critical operational aspects such as whether this is a read-only operation, any rate limits, authentication requirements, data freshness guarantees, or potential errors. For a real-time data tool, these omissions are significant.

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 efficiently structured with a clear purpose statement followed by a bulleted list of return fields. Every sentence adds value, though the second sentence could be slightly more concise by integrating the bullet list introduction more smoothly.

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?

Given the tool's moderate complexity (real-time data retrieval with detailed metrics), no annotations, and no output schema, the description does a reasonable job explaining what data is returned. However, it lacks important context about operational behavior, data sources, update frequency, and error conditions that would be needed for robust agent usage.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on output semantics instead, detailing the structure and meaning of returned statistics. This exceeds the baseline expectation for a parameterless tool.

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

Purpose5/5

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

The description clearly states the tool's purpose with specific verbs ('obtain', 'returns') and resources ('real-time 5-second trading statistics'), including detailed metrics like order volumes and transaction counts. It effectively distinguishes itself from sibling tools by focusing on high-frequency interval data rather than daily, monthly, or company-specific information found in other tools.

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 explicit guidance on when to use this tool versus alternatives. While the focus on 'real-time 5-second' data implies it's for current market snapshots, there's no mention of specific use cases, prerequisites, or comparisons to sibling tools like get_daily_market_trading_info or get_stock_daily_trading that might offer overlapping functionality.

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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