Cabrini MCP

scan_market

Scan all US stocks on a date for custom criteria (gaps, volume, change). Returns pct_change, range_pct, pct_gap, true_range_pct, volume and volume_ratio per match — criteria in percent (5 = 5%), outputs fractional (0.05 = 5%). $0.10 USDC.

Input Schema

TableJSON Schema

Name	Required	Description
`date`	Yes	YYYY-MM-DD
`limit`	No	Max results (default 50)
`gap_up_pct`	No	Min gap up % from prior close
`volume_min`	No	Min total volume
`gap_down_pct`	No	Min gap down % from prior close
`range_pct_min`	No	Min intraday range (high-low)/open as a percent, e.g. 5 for 5%
`change_pct_max`	No	Max intraday change %
`change_pct_min`	No	Min intraday change %
`volume_ratio_min`	No	Min volume vs prior day (e.g. 2.0)

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedJul 27, 2026

addedInput schema / properties / range_pct_min

Added value: +{
+  "description": "Min intraday range (high-low)/open as a percent, e.g. 5 for 5%",
+  "type": "number"
+}

Changed1 schema field changedJul 10, 2026

changedInput schema / properties / limit / description

Previous value: -"Max results (default 50, max 200)"New value: +"Max results (default 50)"

AddedJul 9, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description discloses key behaviors: it lists the exact return fields (pct_change, range_pct, pct_gap, true_range_pct, volume, volume_ratio), clarifies unit conventions (criteria in percent, outputs fractional), and notes the cost ($0.10 USDC). This goes beyond the schema, though it does not mention pagination or rate limits.

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 three sentences, each conveying essential information: purpose, return fields, and unit/cost details. It is front-loaded, efficient, and contains no redundancy or filler.

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

Completeness4/5

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

Given no output schema and no annotations, the description compensates by listing the return fields and unit conventions. It covers the main use case (custom criteria, date-based scan) and cost, but lacks details on pagination or edge cases like conflicting criteria. The schema covers parameter meanings and default limit, so overall it is fairly complete.

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

Parameters4/5

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

The schema already documents all 9 parameters with descriptions (100% coverage), providing a baseline of 3. The description adds valuable cross-parameter context: criteria are in percent (5 = 5%) while outputs are fractional (0.05 = 5%), which clarifies unit conversions not fully evident from individual schema descriptions.

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 'Scan all US stocks on a date for custom criteria (gaps, volume, change)', identifying the exact action and scope. It distinguishes from sibling data-retrieval tools by focusing on market-wide screening rather than per-ticker queries.

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 provides clear context for when to use this tool: when you need to screen all US stocks on a specific date with custom criteria. It does not explicitly mention alternatives, but the market-wide scope inherently contrasts with sibling tools like get_bars or query_range, making the intended usage evident.

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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