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flopsindex-mcp

flopsindex-mcp

by zeroatflops
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_index

Resolve a FLOPS index ID to its public citation payload, including value, unit, and verification URLs. Get the data needed to cite GPU rental price indices.

Instructions

Resolve a FLOPS index to its source-opaque PUBLIC payload (the public citation contract). Returns {index_id, value, unit, as_of, data_tier, confidence, verify_url, citation_url, permalink}. Prefer this when you intend to CITE the value. Also exposed as the MCP resource flops://index/<INDEX_ID>.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "index_id": "<index_id>"
    },
    "name": "get_index"
  }
}

Input Schema

NameRequiredDescriptionDefault
index_idYesFLOPS index id / slug, e.g. 'FLOPS-H100-OD' or 'FLOPS-A100-SPOT'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.12.5

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the transparency burden. It discloses that the payload is 'PUBLIC' and 'source-opaque,' describes the exact return shape, and introduces the resource alias. While it doesn't discuss auth or rate limits, the non-mutating 'Resolve' semantics and public framing provide strong behavioral context.

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 three dense sentences with no filler: it states the core action, lists the return fields, gives a usage preference, and mentions the MCP resource alias. Every sentence adds value.

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

Completeness5/5

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

For a single-parameter tool with no output schema, the description is remarkably complete. It covers the return format, the intended use case, the public nature of the payload, and even the resource URI equivalent. No critical operational context appears missing.

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?

The input schema already covers the single parameter fully with description and an example, so schema coverage is 100%. The description does not add parameter-level detail, which is acceptable because the schema handles it; the baseline score of 3 applies.

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?

The description uses a specific verb ('Resolve') and clearly identifies the resource ('a FLOPS index to its source-opaque PUBLIC payload'), explicitly framing it as the 'public citation contract.' This distinguishes it from siblings like get_price and verify by focusing on the citation-oriented payload.

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?

The description gives explicit guidance: 'Prefer this when you intend to CITE the value.' It does not explicitly name alternative tools or provide when-not-to-use conditions, but it establishes a clear use case in context of sibling 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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