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Agent Data API

memecoin_screen

Memecoin screener for trading agents: your own strategy over the live market (every pump.fun launch in real time + DEX pools on Solana and Base). Filter and sort on 100+ fields in 5m/15m/30m/1h/6h/24h windows: buyers, buy ratio, volume, price change, holders, top-10 %, dev sold %, snipers, bundles, curve progress, liquidity, socials, RugCheck risks, smart money. Presets included. Poll with the cursor. Price: $0.01 per call (x402, USDC).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNo
limitNo
sinceNo
chainsNo
presetNo
filtersNo
sourcesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose valuable traits beyond the schema: real-time data sources, cursor-based polling, and a $0.01/call x402 USDC payment requirement. It omits rate limits, error behavior, and whether results are read-only snapshots, leaving meaningful gaps for a paid live-data tool.

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

Conciseness4/5

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

Front-loaded with the core purpose, then data coverage, filterable fields, presets, polling, and pricing—each clause adds information. Dense but well-organized, no filler sentences.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter, nested-filter tool with no output schema, the description covers intent, data scope, cost, and polling but leaves the mechanics of most parameters and the shape of returned results unspecified. An agent can understand what the tool is but not fully how to construct a correct call.

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

Parameters2/5

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

Schema coverage is 0% across 7 parameters including a nested filters object, so the description must compensate. It hints at filters/sort (100+ fields, presets, time windows) and implies the cursor maps to a param, but never explains the format of sort, limit, chains, sources, or the structure of the filters object. Substantial gaps remain.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: a memecoin screener over live pump.fun launches and Solana/Base DEX pools, with custom strategy and 100+ filterable fields. It is clearly differentiated from siblings like token_launches or memecoin_watch by emphasizing multi-chain live screening with custom filters, though it never explicitly names a sibling to prefer.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Poll with the cursor" and "Presets included" give partial usage cues, and the trading-agent framing implies the context. But there is no explicit when-to-use vs when-not, and no routing to alternatives like token_pretrade_check or memecoin_alerts for single-token or alert use cases.

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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