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trading-mcp-server

trading-mcp-server

by mukul8896
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

calculate_target_price

Compute the target price for a trade based on entry price, stop loss, and a desired risk-reward ratio.

Instructions

Target price for a desired risk:reward given entry and stop.

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": {
      "entry_price": "<entry_price>",
      "stop_loss": "<stop_loss>"
    },
    "name": "calculate_target_price"
  }
}

Input Schema

NameRequiredDescriptionDefault
entry_priceYes
stop_lossYes
risk_reward_ratioNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It implies a non-destructive calculation but does not explicitly state side effects, authentication needs, or that it returns a computed value without modifying state. For a simple calculation, this is acceptable but not thorough.

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 a single 12-word sentence, efficiently front-loaded with the output ('Target price') followed by inputs. Every word adds value, though it could be slightly expanded without losing conciseness.

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 output schema, the description does not specify the return format (e.g., a number). It also lacks details on edge cases or assumptions, making it incomplete for an agent to fully understand the tool's behavior.

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

Parameters2/5

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

The description mentions 'entry', 'stop', and 'risk:reward' but does not explain each parameter's role beyond the schema title. With 0% schema description coverage, the description should elaborate on risk_reward_ratio's meaning and default, which it fails to do.

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 precisely states the tool's output ('Target price') and its inputs ('entry and stop' and 'desired risk:reward'), clearly distinguishing it from sibling tools like calculate_position_size or calculate_stop_loss.

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 given on when to use this tool versus alternatives (e.g., calculating stop loss or position size). The description merely states what it does, without any context on prerequisites or exclusions.

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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