Skip to main content
Glama

stox-mcp

by io.github.nirajagarwal

Metric screen (P3-sorted, min/max on all 16 scores)

screen
Read-only

Screen the S&P 500 + NDX universe on ANY of the 16 percentile scores, with minimum AND maximum bounds, optionally within one GICS sector, sorted by the validated P3 composite or by any single metric. Metric keys: marketBeat1Y/1M/1W/1D (price vs SPY), rankPersistence52W/26W/13W + trendPersistence (rank stability), businessBeat + revGrowthYoy + marginGrowthYoy + fcfGrowthYoy (business growth), accumDistFlow/30/5/2 (money flow 60/30/5/2-day). Examples: momentum — {sort_by:'marketBeat1M', filters:[{metric:'businessBeat', min:70}]}; fallen leaders — {filters:[{metric:'rankPersistence52W', min:80},{metric:'marketBeat1Y', max:40}]}. Legacy min_perform/min_persist/min_profit/min_pressure still work (the four headline scores).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNomax results (default 12)
sectorNoGICS sector filter, e.g. 'Energy'
filtersNobounds on any metrics; entries AND together
sort_byNo'p3' (default) or any metric key; descending
min_profitNo
min_performNo
min_persistNo
min_pressureNo

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds useful behavioral nuance: filters AND together, sorting can be by P3 or a single metric, and legacy parameters still work. This goes beyond the structured annotations without contradicting them.

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 dense but every section earns its place: core behavior, metric-key vocabulary, and two illustrative examples. It is front-loaded with the main purpose and avoids 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?

The description covers the key input semantics, metric vocabulary, legacy compatibility, and example payloads well enough for correct invocation. With no output schema, it could optionally describe the response shape, but that omission is minor for a screening tool whose parameters and selection logic are thoroughly specified.

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 description coverage is only 50%, but the description compensates by enumerating all 16 metric keys, explaining sort behavior, giving full filter examples, and naming the four legacy parameters. This adds meaningful semantics beyond the bare schema, though n and sector remain primarily documented by the schema.

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 opens with a specific verb ('Screen'), a precise universe ('S&P 500 + NDX'), and a clear object ('ANY of the 16 percentile scores' with min/max bounds and sorting). The metric-key enumeration and examples make the tool's function unambiguous and distinguishable from sibling tools like compare or peers.

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 clearly states what universe and filtering dimensions the tool operates on, and gives two concrete usage examples. It does not explicitly name sibling tools or state when not to use them, but the context is strong enough that an agent can infer screening use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All stox-mcp toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.3/5.0
Disambiguation5/5

Each tool owns a distinct analytical niche: single-stock character, multi-ticker comparison, market regime, business peers, co-movement cluster, and universe screening. The only near-overlap (fingerprint's peer list vs peers) is explicitly resolved by describing peers as the deeper standalone lookup.

Naming Consistency3/5

All names are lowercase and stylistically consistent, but there is no verb_noun pattern: compare and screen are verbs while market_regime, peers, and theme_cluster are noun phrases. The mixed grammar is readable but not a strongly predictable naming convention.

Tool Count5/5

Six tools is tightly scoped for a stock-character research server; each tool covers a distinct user workflow and none feels redundant. The count is well within the ideal range and does not burden an agent with overlapping endpoints.

Completeness5/5

The set covers the full intended workflow: assess market context, inspect a single stock, compare tickers, identify true peers and co-movement groups, and screen the universe on every available metric. There are no obvious dead ends or missing operations for a read-only analytics domain.

Resources