Skip to main content
Glama

Stocklake — AI Stock Intelligence

by dev.stocklake.api
OverviewDiscussionsAdmin

Get Market Movers

get_market_movers
Read-onlyIdempotent

Top market movers from the Stocklake universe — gainers, losers, most active.

  • category: "gainers" | "losers" | "most_active" | "all" (default "all" = all 3 categories)

  • limit: results per category (default 10, max 20). Each returned stock counts as one call toward your daily limit — a symbol appearing in more than one category (e.g. both "gainers" and "most_active") counts once per category it appears in.

  • min_market_cap_b: filter to stocks above this market cap in billions of US dollars (e.g. 1.0 = $1B+), compared against market_cap_usd

Returns per stock: symbol, name, sector, price, change_pct, volume, rsi, market_cap (listing currency), market_cap_usd, currency, analyst_rating, atr_pct (atr_pct omitted when the underlying volatility reading is missing or corrupted). Available to all tiers.

Pro tier adds the minimum AI-narrative slice (ai_verdict, ai_headline, ai_score 0-100, ai_score_band) — precomputed, no extra AI cost. A big mover's price/volume/RSI alone doesn't say whether the move matters; the one-line headline does. For the full research bundle on any one mover, call get_stock_research(symbol).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoResults per category (default 10, max 20). Each returned stock counts as one call toward your daily limit — a symbol appearing in more than one category (e.g. both "gainers" and "most_active") counts once per category it appears in.
categoryNoWhich movers category to return: "gainers" | "losers" | "most_active" | "all" (default "all" = all 3 categories).all
min_market_cap_bNoFilter to stocks above this market cap in billions of US dollars, e.g. 1.0 = $1B+ (compared against market_cap_usd).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / min_market_cap_b / description
      Previous value: -"Filter to stocks above this market cap in billions of dollars, e.g. 1.0 = $1B+."New value: +"Filter to stocks above this market cap in billions of US dollars, e.g. 1.0 = $1B+ (compared against market_cap_usd)."
  2. Changed3 schema fields changed
    • addedInput schema / properties / category / description
      Added value: +"Which movers category to return: \"gainers\" | \"losers\" | \"most_active\" | \"all\" (default \"all\" = all 3 categories)."
    • addedInput schema / properties / limit / description
      Added value: +"Results per category (default 10, max 20). Each returned stock counts as one call toward your daily limit — a symbol appearing in more than one category (e.g. both \"gainers\" and \"most_active\") counts once per category it appears in."
    • addedInput schema / properties / min_market_cap_b / description
      Added value: +"Filter to stocks above this market cap in billions of dollars, e.g. 1.0 = $1B+."
  3. Added

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds substantial behavioral detail: the daily call-limit counting per category, the omission of atr_pct when volatility data is missing/corrupted, and tier-dependent output (Pro adds AI-narrative slice). These are beyond what annotations provide and are clearly disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with bullet points and front-loaded purpose, but it is quite long and repeats information already present in the input schema. The parameter bullet list is redundant with the schema descriptions, and the tier explanation could be tightened. It is not maximally concise, though it is organized.

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?

The description fully covers what the tool returns (per-stock fields), explains tier differences, discloses the call-count impact, and points to a follow-up tool. Since an output schema exists, return-value details are further reinforced. An agent has everything needed to decide when and how to invoke this tool correctly.

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 description coverage is 100%, so the schema already documents all three parameters with examples and default values. The tool description's bullet list essentially duplicates the schema text (e.g., the limit counting, the market-cap example). It does not introduce new meaning beyond the schema, so it meets the baseline but adds no extra value.

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 resource (market movers from the Stocklake universe) and the specific categories (gainers, losers, most active). It distinguishes from siblings like get_stock, get_stocks, and get_screener by focusing on top movers. The verb 'get' and resource 'market movers' are explicit and unambiguous.

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 names an alternative tool (get_stock_research) for deeper research on a single mover, giving clear guidance for when to step beyond this tool. It also notes tier availability, but does not explicitly enumerate when to use this versus other list-oriented tools like get_screener or get_signals. However, the context of 'top movers' implicitly directs usage.

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

All Stocklake — AI Stock Intelligence toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources