Skip to main content
Glama

Birdeye Gainers Losers

birdeye_gainers_losers
Read-onlyIdempotent

Top trader gainers/losers. Returns the ranked list of wallets by realized/unrealized PnL over a time window (yesterday/today/1W/30d/90d). Example: birdeye_gainers_losers({ type: "1W", sort_by: "PnL", chain: "solana", _apiKey: "your-key" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoTime window for PnL ranking: "yesterday", "today", "1W", "30d", or "90d". Defaults to "1W".
chainNoBlockchain to query (sent as the x-chain header). Defaults to "solana".
limitNoNumber of traders to return (1–50, default 20).
_apiKeyYesBirdeye API key (get one at birdeye.so; limited free tier).
sort_byNoRanking metric: "PnL", "realized_pnl", or "unrealized_pnl". Defaults to "PnL".
sort_typeNo"desc" (top gainers, default) or "asc" (top losers).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive behavior, so the safety profile is covered. The description adds useful context about the time window and PnL metrics, but it does not explain details like response structure, pagination, rate limits, or default behaviors beyond the schema. This is adequate but not rich.

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 compact and front-loaded, with no filler. The first sentence states the core behavior and the second provides a realistic invocation example. Every piece of text earns its place.

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?

For a read-only list tool with fully documented parameters and a complete example call, the description is nearly sufficient. The only notable gap is the lack of any detail about the response shape or field semantics when no output schema is present, but the description still gives enough context to invoke the tool successfully.

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 every parameter already has a meaningful description. The tool description itself does not add significant parameter-level detail beyond what the schema provides, though the example call demonstrates a valid combination. Baseline 3 is appropriate since the schema does the heavy lifting.

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 uses a specific verb ('Returns') and a specific resource ('ranked list of wallets by realized/unrealized PnL over a time window'), making the tool's function immediately clear. It also lists the valid time windows and an example call, distinguishing it from sibling token-specific Birdeye tools like birdeye_token_holders and birdeye_token_overview.

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 establishes the tool's context: ranking wallets by PnL for specified periods. It does not explicitly say when not to use it or name alternative tools, but the strong resource and metric framing makes the intended use obvious relative to the sibling token-focused tools. There are no exclusions, but the context is clear enough for an agent to select it appropriately.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.