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Curo Peptide Research MCP: PepBank Studies, Peptide Lookup and Lab Reports (COAs)

Use and dose

use_and_dose
Read-onlyIdempotent

Read what community sources report about how people use one peptide: uses, route, amount, frequency, duration, reported effects and cautions, each line with its sources. Also read the doses from published studies, with species, route, study design and source. Community reports are not tested in trials. Use it for use, dose or cycle questions. Use peptide_research for what the studies found. A peptide can have no record.

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": {
      "peptide": "<peptide>"
    },
    "name": "use_and_dose"
  }
}

Input Schema

NameRequiredDescriptionDefault
peptideYesPeptide name or slug, for example BPC-157 or tb-500.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, open-world, non-destructive, so the safety profile is covered. The description still adds real behavioral context: every line carries its sources, community reports are not trial-tested, and a peptide may have no record at all. It stops short of describing result size, truncation, or ordering.

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?

Content is front-loaded: what is returned, then the reliability caveat, then the routing rule, then the empty-result case. It is dense but nearly every clause earns its place; the long enumeration in the first sentence makes it feel run-on and could be trimmed.

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?

For a one-parameter read tool with no output schema, the description covers return content, provenance, a trust caveat, the sibling alternative, and the no-record case. An agent has enough to call it and interpret empty results; only result format/pagination detail is absent.

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?

With a single 100%-covered parameter, the schema already documents that 'peptide' takes a name or slug with examples. The description only reinforces the single-peptide scope ('one peptide'), adding little syntax or lookup guidance beyond the schema. Baseline 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 states a specific verb and resource: read community-reported use (uses, route, amount, frequency, duration, effects, cautions) plus study doses for ONE named peptide. It explicitly names the sibling peptide_research and explains how this tool differs, so an agent can route without opening either schema.

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

Usage Guidelines5/5

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

It gives an explicit trigger ('use, dose or cycle questions') and an explicit alternative with its condition ('Use peptide_research for what the studies found'). That is a clear when-to-use and when-to-use-the-other split.

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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