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@blockchainacademics/mcp

@blockchainacademics/mcp

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by blockchainacademics
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TypeScript
Remote

get_compute_pricing

Get GPU pricing for Akash, Render, and IO.net networks. Filter by GPU type like A100 or H100 to compare compute costs.

Instructions

Akash, Render, IO.net pricing per GPU type.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_compute_pricing"
  }
}

Input Schema

NameRequiredDescriptionDefault
gpuNoGPU type filter (e.g. 'A100', 'H100').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description must compensate. It does not mention whether the data is real-time, cached, requires authentication, or has usage limits. The phrase 'pricing per GPU type' implies a static lookup, but behavioral details are absent.

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?

The description is very concise at 6 words, efficiently conveying the core purpose. However, it lacks structure (e.g., no separate sentences for usage) and could expand slightly to include key details without losing brevity.

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

Completeness2/5

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

Given no annotations or output schema, the description should provide more context about expected output behavior, defaults, and prerequisites. For a simple tool, it is incomplete—an agent would need to infer or test to understand how to use it properly.

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% as the single parameter 'gpu' has a description with examples. The description adds context by naming the providers, but does not explain the parameter's effect on the response (e.g., if omitted, returns all GPU types). This is adequate but not exceptional.

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 it provides pricing per GPU type for Akash, Render, and IO.net. It distinguishes itself from other tools in the list, as no sibling tool offers compute pricing. However, it could be more specific about the action (e.g., 'Retrieve pricing') and the scope.

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?

No guidance is provided on when to use this tool vs alternatives. The sibling tools include many listing and analysis tools, but no direct substitute is mentioned. An agent might not know if this is the correct tool for GPU cost comparison.

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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