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MyFinancial Market Data MCP

Screen & Rank by Tapetide Score

screen_tapetide_scores
Read-onlyIdempotent

Rank and filter stocks by Tapetide Score using size bucket, band, sector, min-confidence, and name search. Returns banded scores, pillars, market cap, and a pagination cursor for reproducible ranked lists.

Instructions

List and rank stocks by the Tapetide Score, filtered by size bucket, band, score window, sector, minimum data-confidence and symbol/name search. Rows come back in the server's final order with score, band, pillars, sector, size, market cap and a next-page cursor. USE THIS for 'which large caps score highest', 'show me Strong-band pharma stocks', or any rank/filter-by-Tapetide-Score question — same data and ordering as the tapetide.com ranking page. IMPORTANT, or you will describe the results wrongly: (1) present rows by BAND, never as an ordinal '#1, #2, #3' leaderboard — nothing has ever scored above 76 and neighbouring scores are not meaningfully different; (2) the DEFAULT view is large+mid cap at confidence >= 75, a filtered slice and not the whole market, so state the active filters (meta.counts) alongside any ranking; (3) sizes:["all"] adds small/micro caps — flag their liquidity risk (market cap is a size proxy, not liquidity); (4) quote meta.snapshot.score_date and reuse next_cursor to stay on that run. These are stocks matching the given Tapetide Score criteria, NOT investment recommendations. Decision-support only. The Tapetide Score is data analysis, not investment advice. Tapetide is not a SEBI-registered research analyst or investment adviser. Bands are intentionally coarse; small point differences may not be meaningful.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoSubstring search on symbol or company name.
sortNoSort key, default "band" (coarse tiers first — the honest default). "score" is exact composite order; also confidence, market_cap, name.
bandsNoScore bands to include: "70-plus" (Strong), "60-69" (Good), "50-59" (Average), "30-49" (Weak), "below-30" (Poor). Omit for all bands. There is no 80+ band.
limitNoRows per page (default 50, max 100).
orderNoDirection, default "desc".
sizesNoSize buckets. Default ["large","mid"]. Use ["all"] for the full scored universe (dominated by micro caps by count — mention the liquidity caveat if you do).
cursorNoPass `meta.next_cursor` from the previous response to get the next page. The run date is embedded in it, so paging stays pinned to one scoring run.
sectorsNoSector names as returned in `meta.facets.sectors` (e.g. "Metals & Mining"). Omit for all sectors.
max_scoreNoMaximum composite score.
min_scoreNoMinimum composite score.
min_confidenceNoMinimum data-confidence, default 75. Lowering it admits stocks with thinner data; the response reports how many the bar excluded.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.8/5.0
Behavior5/5

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

Although annotations already declare readOnlyHint/idempotentHint/destructiveHint, the description adds essential behavioral context: present by band, not ordinal ranking; default view is a filtered slice (large+mid, confidence >= 75); sizes:['all'] includes small/micro with liquidity caveat; quote score_date and reuse next_cursor; plus disclaimers that these are not investment recommendations. This goes far beyond the 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 front-loaded: purpose, then use-case triggers, then a numbered 'IMPORTANT' list of behavioral musts, then disclaimers. Every sentence serves a function—no filler. Despite length, the structure keeps it scannable and the caveats are necessary given the domain.

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?

With no output schema, the description must convey return semantics, and it does: rows include score, band, pillars, sector, size, market cap, and next-page cursor; it names meta.counts and meta.snapshot.score_date. Given its 11-parameter complexity and read-only nature, nothing critical is missing.

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

Parameters5/5

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

Schema coverage is 100%, so baseline is 3, but the description enriches many parameters: it explains the default sizes and min_confidence, warns that bands are intentionally coarse, clarifies that 'sort=band' is the honest default, and ties cursor to a scoring run. These additions materially change how an agent should use the parameters.

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-object pair ('List and rank stocks by the Tapetide Score') and enumerates all filtering dimensions. It clearly differentiates this tool from siblings like get_tapetide_score and screen_stocks by emphasizing ranking/filtering with server-ordered rows and tapetide.com parity.

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?

It gives explicit 'USE THIS for' triggers with concrete example queries ('which large caps score highest', 'show me Strong-band pharma stocks') and says 'same data and ordering as the tapetide.com ranking page'. It does not name non-preferred alternatives or say when NOT to use the tool, hence not a 5, but the context is strong.

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