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mcp-knowledge

by io.github.getgapup

x402_liquidity_monitor

Read-onlyIdempotent

Monitors real-time x402-USDC liquidity depth across 12 decentralized and centralized exchanges, providing slippage alerts and depth analysis for CFO liquidity risk assessment. Inputs include slippage thresholds and exchange selection; outputs liquidity depth, price impact estimates, and warning flags. Essential for optimizing trade execution and managing liquidity exposure. Keywords: liquidity monitoring, slippage analysis, DEX/CEX depth, x402-USDC pair, CFO financial tooling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf 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.
exchangesNoList of exchanges to monitor (defaults to all 12 if empty)
depthLevelsNoLiquidity depth levels to analyze (percentage from mid-price)
slippageThresholdYesMaximum acceptable slippage percentage (0-100)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesYes
midPriceNoCurrent x402-USDC mid-price
warningsYes
priceImpactNo
liquidityDepthYes
slippageAlertsYes

TDQS

A4/5.0
Behavior4/5

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

Annotations already indicate readOnly, openWorld, and idempotent behavior. The description adds value by detailing outputs (liquidity depth, price impact, warning flags) and the real-time nature. It does not contradict annotations, but could further clarify data freshness or caching.

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 three sentences: purpose, inputs/outputs, and keywords. It is mostly concise, though the final keywords line adds marginal value. It fronts the core information effectively.

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 (real-time monitoring across 12 exchanges) and that both input schema and output schema are fully described, the description adequately covers purpose, usage context, and high-level behavior. No critical gaps remain.

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 coverage is 100% with descriptions for all parameters. The description merely repeats 'slippage thresholds and exchange selection' without adding new meaning or usage details beyond the schema, meeting the baseline for high coverage.

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 specifies the action ('monitors'), the resource ('x402-USDC liquidity depth across 12 exchanges'), and the outputs ('slippage alerts and depth analysis'). It distinguishes this tool from siblings like x402_payment_flow_analyzer by focusing on liquidity depth monitoring for CFO risk assessment.

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

Usage Guidelines3/5

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

The description states it is 'essential for optimizing trade execution and managing liquidity exposure' and implies usage for liquidity risk assessment, but it does not explicitly compare to alternative tools or specify when not to use it. Among numerous siblings, more explicit guidance would be beneficial.

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.

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