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Search Dappradar Rankings

search_dappradar_rankings
Read-only

Top 50 dapps from DappRadar's public rankings page: rank, name, token symbol, chains, market cap, token price, price change, trading volume, unique active wallets (UAW) and TVL, for 24h/7d/30d, optionally for one chain (eth, solana, bnb, base, polygon, arbitrum, tron...). Values in USD as shown by DappRadar; missing values are null. Public page, no key. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNoDappRadar chain slug, e.g. eth, solana, bnb, base, polygon, arbitrum, avalanche, tron, ton (optional, default all chains)
limitNoHow many dapps, 1 to 50 (default 25)
periodNo24h, 7d or 30d (default 24h)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNo
countNo
dappsNo
periodNo
sourceNo
checkedAtNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations only declare readOnly and openWorld; the description adds substantive context the agent cannot get elsewhere: it is a public page requiring no key, costs $0.002 USDC per successful call via x402 on Base/Solana/Arc, failed calls are free, and missing values come back as null.

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?

A single dense but well-ordered block: resource and scope first, then field list, then filtering, then data semantics, then pricing. Nothing is redundant, though the run-on structure makes the key facts slightly harder to scan.

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?

With an output schema present and 100% parameter documentation, the description need only carry cost, access and data-quality semantics, which it does. The only gap is sibling differentiation, which matters here given the crowded rankings/news namespace.

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 coverage is 100%, so all three parameters and their defaults are already documented in structured form. The description adds value at the result level (USD values, null semantics) but contributes little parameter-specific meaning beyond what the schema states.

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?

States a specific verb (search/retrieve rankings) plus resource (DappRadar's top-50 dapp rankings) and enumerates the returned fields, so an agent can distinguish it from the many news/academic/ranking siblings instantly.

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?

Usage context is implied (a public, paid rankings lookup), and chain filtering is described, but there is no explicit 'use this instead of X' routing or statement of when not to use it. The agent has to infer that this is the dapp-metrics source rather than a general crypto search.

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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