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tdnupe3

Coin Railz MCP Server

by tdnupe3
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

detect_fraud

Analyze transaction data to identify fraudulent activity, providing fraud scores, risk indicators, and actionable recommendations for blockchain transactions.

Instructions

AI-powered fraud detection for transactions.

Args: transaction_data: Transaction details to analyze

Returns: Fraud score, risk indicators, and recommendations.

Price: $0.50

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
transaction_dataYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • coinrailz_mcp/__init__.py:766-780 (handler)
    The detect_fraud tool is defined here using the @mcp.tool() decorator. It calls the underlying 'fraud-detection' service via call_coinrailz_service and returns the result as a formatted JSON string.
    @mcp.tool()
async def detect_fraud(transaction_data: dict) -> str:
    """
    AI-powered fraud detection for transactions.
    
    Args:
        transaction_data: Transaction details to analyze
    
    Returns:
        Fraud score, risk indicators, and recommendations.
    
    Price: $0.50
    """
    result = await call_coinrailz_service("fraud-detection", transaction_data)
    return json.dumps(result, indent=2)

Tool Definition Quality

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions 'AI-powered' and 'Price: $0.50,' which hints at computational cost and potential external API usage, but lacks critical behavioral details like rate limits, authentication requirements, error handling, or whether it's read-only or mutative.

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 appropriately sized and front-loaded, with the core purpose stated first. However, the 'Price: $0.50' line, while useful, could be integrated more smoothly, and the structure with separate 'Args' and 'Returns' sections is clear but slightly verbose for such brief content.

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 complexity (AI-powered analysis with nested input objects), lack of annotations, and 0% schema coverage, the description is incomplete. It mentions output ('Fraud score, risk indicators, and recommendations'), which is helpful since an output schema exists, but fails to address input requirements or behavioral constraints adequately.

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?

Schema description coverage is 0%, with one parameter ('transaction_data') documented only as an object with 'additionalProperties: true.' The description adds minimal semantics by naming it 'Transaction details to analyze' but doesn't specify required fields, formats, or examples, leaving the parameter largely undefined.

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 the tool's purpose as 'AI-powered fraud detection for transactions,' which is a specific verb ('detect') + resource ('fraud') combination. However, it doesn't differentiate from sibling tools like 'get_credit_risk_score' or 'run_compliance_check,' which might have overlapping financial risk assessment domains.

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. The description mentions analyzing 'transactions' but doesn't specify context (e.g., payment processing, blockchain transactions) or exclusions, leaving the agent to infer usage from the tool name alone.

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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