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trading-mcp-server

trading-mcp-server

by mukul8896
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

calculate_sma

Compute the latest simple moving average (SMA) value for a given symbol, period, and timeframe. Use this technical analysis tool to identify trends and support/resistance levels.

Instructions

Simple moving average (latest value).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "symbol": "<symbol>"
    },
    "name": "calculate_sma"
  }
}

Input Schema

NameRequiredDescriptionDefault
symbolYes
periodNo
timeframeNoONE_DAY

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.3/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does not mention whether the tool is read-only, requires specific data availability, or what happens if the symbol is not found. A minimal indication of side effects or safety is missing.

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

Conciseness2/5

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

The description is extremely concise with only two words plus a parenthetical, but it sacrifices necessary detail. It is under-specified and does not earn its brevity, as key information about parameters and usage is omitted.

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

Completeness1/5

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

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is critically incomplete. It does not describe return values, required data freshness, or error handling, leaving the agent without essential context to use the tool correctly.

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

Parameters1/5

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

The input schema has 3 parameters with 0% schema description coverage, and the description does not explain any parameter purpose. 'Symbol', 'period', and 'timeframe' are not elaborated, leaving the agent to infer meaning from names alone. This is insufficient for correct parameter selection.

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 it calculates the latest simple moving average, matching the tool's name and indicating the specific value returned. However, it does not differentiate from sibling tools like calculate_ema or calculate_rsi, which are also technical indicators.

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 is provided on when to use this tool versus alternatives such as calculate_ema or calculate_macd. The description lacks any context about prerequisites, typical use cases, or limitations.

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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