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TypeScript

Hybrid

Screen Companies

screen_companies

Read-only

Screen companies by price, volume, cash runway, float, shares, market cap, industry, exchange, and float source. Sort results, view trading-halt status, and exclude halted tickers.

Instructions

Screen companies by price range, volume, cash runway, float, shares outstanding, market cap, industry, listing exchange (NASDAQ/NYSE/AMEX), and float data source. Sort results by any sortable column. Returns matching companies with key metrics and pagination. Each row carries live trading-halt status (halted/haltCode/haltedAt; false/null when trading normally); pass excludeHalted=true to drop currently-halted tickers from the results.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum results per page (default: 25, max: 100)
`offset`	No	Offset for pagination (default: 0)
`sortBy`	No	Column to sort results by (default: volume)
`country`	No	Company universe by issuer domicile: "US" (default), "CA" (Canadian companies via their US-OTC/US cross-listings), or "all"
`exchange`	No	Filter by listing exchange (exact match): NASDAQ, NYSE, or AMEX
`industry`	No	Filter by company industry (exact match, e.g. "Biotechnology", "Software")
`maxFloat`	No	Maximum computed public float (shares)
`maxPrice`	No	Maximum latest price in USD
`minFloat`	No	Minimum computed public float (shares)
`minPrice`	No	Minimum latest price in USD
`maxVolume`	No	Maximum daily trading volume
`minVolume`	No	Minimum daily trading volume
`sortOrder`	No	Sort direction (default: desc)
`floatSource`	No	Filter by float data source
`excludeHalted`	No	When true, exclude tickers with a currently-active trading halt (regulatory or volatility) from the results. Default false — halted rows are included and carry halted/haltCode/haltedAt fields.
`maxCashRunway`	No	Maximum estimated months of cash remaining
`minCashRunway`	No	Minimum estimated months of cash remaining
`maxMarketCapComputed`	No	Maximum market cap in USD (price * shares outstanding)
`maxSharesOutstanding`	No	Maximum shares outstanding from SEC EDGAR
`minMarketCapComputed`	No	Minimum market cap in USD (price * shares outstanding)
`minSharesOutstanding`	No	Minimum shares outstanding from SEC EDGAR

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.1.2Sep 23, 2026

addedInput schema / properties / exchange

Added value: +{
+  "description": "Filter by listing exchange (exact match): NASDAQ, NYSE, or AMEX",
+  "type": "string"
+}

Changed2 schema fields changedv0.1.1Jul 17, 2026

addedInput schema / properties / country

Added value: +{
+  "description": "Company universe by issuer domicile: \"US\" (default), \"CA\" (Canadian companies via their US-OTC/US cross-listings), or \"all\"",
+  "enum": [
+    "US",
+    "CA",
+    "all"
+  ],
+  "type": "string"
+}

addedInput schema / properties / excludeHalted

Added value: +{
+  "description": "When true, exclude tickers with a currently-active trading halt (regulatory or volatility) from the results. Default false — halted rows are included and carry halted/haltCode/haltedAt fields.",
+  "type": "boolean"
+}

First observedv0.1.0Jul 1, 2026

TDQS

A4.4/5.0

Behavior4/5

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

The description adds behavioral context beyond the readOnlyHint annotation, such as the presence of trading-halt fields in results and the option to exclude halted tickers. It also mentions default pagination and sorting. 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 concise, with two main sentences covering purpose and details, plus a third for halt behavior. It front-loads the core function and uses an efficient structure.

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 the high schema coverage and presence of an output schema, the description adequately covers the use case. It explains pagination, sorting, and halt filtering, which are critical for using the tool effectively. No major gaps.

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?

Schema coverage is 100%, so parameters are individually documented. The description adds value by summarizing the screening dimensions and highlighting the halt behavior, which is not evident from parameter descriptions alone. It groups related parameters conceptually.

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 screens companies by multiple criteria (price, volume, cash runway, etc.) and returns matching companies with key metrics and pagination. It distinguishes itself from sibling tools (e.g., get_company_profile, search_companies) by being a multi-filter screener.

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 explains when to use the tool (to filter companies by various financial and trading attributes) and provides details about controlling halt status and pagination. It does not explicitly state when not to use it or list alternatives, but the context is clear and the feature set is well-defined.

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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