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qingfeng

DeFi Rates MCP Server

by qingfeng

search_best_rates

Find optimal borrow or supply rates for crypto assets across DeFi protocols to compare lending platforms and identify earning opportunities.

Instructions

Find the best borrow or supply rates for a specific asset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetYesThe asset to search for (e.g., USDC, USDT, WETH)
typeYesWhether to search for best borrow rates (lowest) or supply rates (highest)
chainNoOptional: filter by blockchain
limitNoNumber of results to return (default: 10)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'finds' rates, implying a read-only operation, but doesn't cover critical aspects like rate limits, authentication needs, data freshness, or what 'best' means (e.g., sorted order, criteria). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a tool with clear parameters and no complex output schema, making it easy for an agent to parse quickly.

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?

Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is minimally adequate. It covers the purpose but lacks usage guidelines, behavioral details, and output information. Without annotations or an output schema, the agent is left with gaps in understanding how to interpret results or handle edge cases, making it incomplete for optimal use.

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 fully documents all parameters. The description adds no additional meaning beyond what's in the schema—it mentions 'specific asset' and 'borrow or supply rates', which are already covered by the 'asset' and 'type' parameter descriptions. With high schema coverage, the baseline is 3, as the description doesn't compensate but doesn't detract either.

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?

The description clearly states the tool's purpose: 'Find the best borrow or supply rates for a specific asset.' It specifies the verb ('find'), resource ('rates'), and scope ('specific asset'), distinguishing it from siblings like 'get_latest_rates' or 'compare_platforms' by focusing on best rates. However, it doesn't explicitly differentiate from 'get_earn_markets' or 'calculate_looping_strategy', which might involve rate-related operations, so it's not a perfect 5.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'compare_platforms' or 'get_latest_rates', nor does it specify prerequisites or exclusions. The agent must infer usage from the purpose alone, which is insufficient for optimal tool selection.

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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