mcp-knowledge

x402_payment_flow_analyzer

Read-onlyIdempotent

As a CTO, analyze USDC payment flows involving x402 addresses to assess counterparty risk, trace transaction paths, and evaluate regulatory exposure. Input a wallet address or transaction hash to receive risk scores, flow diagrams, and compliance flags from Chainalysis and TRM Labs public APIs. Ideal for due diligence, fraud detection, and compliance reporting. Pass async:true to avoid timeout.

Input Schema

TableJSON Schema

Name	Required	Description
`async`	No	If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
`depth`	No	Hops to trace in payment flow
`txHash`	No	USDC transaction hash to trace
`address`	Yes	Ethereum wallet address to analyze
`includeRiskScore`	No	Include counterparty risk scoring

Output Schema

TableJSON Schema

Name	Required	Description
`flowId`	No	Unique identifier for this payment flow analysis
`status`	Yes
`sources`	No
`warnings`	No
`riskScore`	No	Counterparty risk score (0-100)
`complianceFlags`	No
`exposureSummary`	No
`transactionPath`	No

TDQS

A4.5/5.0

Behavior5/5

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

The description adds value beyond annotations (readOnlyHint, openWorldHint, idempotentHint) by disclosing use of Chainalysis and TRM Labs public APIs, the nature of outputs (risk scores, flow diagrams, compliance flags), and the async behavior. No contradictions with annotations.

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

Conciseness5/5

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

The description is two sentences: the first states purpose and inputs/outputs, the second covers usage scenarios and a performance tip. No wasted words, and key information is front-loaded.

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

Completeness5/5

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

Given the tool's complexity, the description sufficiently covers its purpose, inputs, outputs, and use cases. An output schema exists, so return values are documented. The description provides enough context for selection among siblings.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description does not add additional meaning beyond the schema's parameter descriptions; it only briefly mentions input types in the purpose statement.

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 analyzes USDC payment flows involving x402 addresses for counterparty risk, transaction tracing, and regulatory exposure. It specifies input types and outputs (risk scores, flow diagrams, compliance flags), distinguishing it from related siblings like x402_payment_fraud_detector or x402_liquidity_monitor.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description notes ideal use cases (due diligence, fraud detection, compliance reporting) and provides an async tip to avoid timeouts. However, it does not explicitly state when not to use this tool or mention alternatives among siblings.

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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TDQS

C2.8/5.0

Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

x402_payment_flow_analyzer

Input Schema

Output Schema

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