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ExchangeRebel — pay-per-call APIs for AI agents (x402 on Solana)

data_bundle

Fetch the ExchangeRebel premium data bundle. $0.05 per call — USDC on Solana via x402 (over MCP: call without payment to get the PaymentRequired challenge, then retry with the payment at _meta["x402/payment"]). HTTP equivalent: GET https://exchangerebel.com/api/data. Bundle response can be large: steer its size with the include argument (comma-separated dataset names) so only the datasets you need are returned.

Input Schema

NameRequiredDescriptionDefault
includeNoComma-separated dataset names

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Discloses behavior well beyond the annotations: a per-call price ($0.05 in USDC on Solana), the exact x402 challenge/retry handshake, an HTTP fallback endpoint, and the warning that responses can be large along with the mitigation. This is the kind of operational detail the readOnlyHint=false annotation implies but does not explain.

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?

Front-loads the purpose, then payment mechanics, then the sizing tip; every sentence carries information an agent needs (cost, handshake, response size). No filler or restatement of the tool name.

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 no output schema, the description correctly covers return-shape concerns by warning about bundle size and how to constrain it, and it covers the payment path fully. The one gap is discoverability of valid dataset names for `include`, which an agent cannot infer from this text alone.

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

Parameters4/5

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

Schema coverage is 100% and the single parameter is optional, so the baseline is 3; the description goes further by explaining that `include` is a comma-separated dataset list used to steer bundle size, implying that omitting it returns everything. It still doesn't say where valid dataset names come from.

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 and resource: "Fetch the ExchangeRebel premium data bundle," which is concrete and distinguishable from generic bundle siblings by the ExchangeRebel qualifier and the premium/x402 framing. It does not explicitly contrast itself with near-neighbors like pack_get or render_bundle, so it falls short of full sibling differentiation.

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?

Gives clear procedural context for invocation: call once to receive the PaymentRequired challenge, then retry with the payment at _meta["x402/payment"], plus guidance to narrow the response with `include`. It offers no when-not-to-use guidance or comparison to alternative data tools.

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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