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Bitcoin Stamps MCP

Stamp Dispensers

stamp_dispensers

Retrieve live counterparty listings for a bitcoin stamp, displaying open quantities, rates, and statuses to identify active offers and the floor price.

Instructions

Counterparty dispensers for a stamp — the on-chain 'listings'. Each row: source/origin address, give_quantity, give_remaining, escrow_quantity, satoshirate and btcrate (price per unit), status (open/closed), tx hash. An open dispenser with give_remaining > 0 is a live offer; the lowest btcrate among them is the floor. Buying is a wallet action by the user — this tool only reads.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
limitNo
stamp_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states the tool only reads and explains the meaning of open/closed and the floor price, which is useful. Yet it omits details like pagination behavior, error conditions, or permission requirements, making the transparency adequate but not thorough.

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 a single paragraph that front-loads the main purpose and then explains the data fields and key concepts. It is concise with no filler, though it could be tightened by trimming redundant phrasing like 'the on-chain listings' after already saying Counterparty dispensers.

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?

For a simple read tool with three parameters and an output schema, the description covers the return data and the read-only nature, but lacks guidance on parameter usage, sibling differentiation, and edge cases (e.g., pagination limits, error handling). These gaps prevent it from being fully complete.

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

Parameters2/5

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

The schema description coverage is 0%, meaning the description does not explain any of the three parameters (stamp_id, page, limit). While stamp_id is implicitly referenced as 'for a stamp', the description does not define the parameter semantics or provide additional meaning beyond the schema's names and types, failing to compensate for the coverage gap.

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 lists Counterparty dispensers for a stamp, describing them as on-chain listings and enumerating the fields returned. It conveys the specific resource (dispensers) and the entity (stamp), but does not explicitly differentiate it from sibling tools like dispensers_by_address or stamp_holders, so it loses a point.

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

Usage Guidelines3/5

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

The description implies usage for reading dispenser listings and explicitly notes that buying is a wallet action, not this tool. However, it does not mention alternatives or conditions for when to choose this tool over others, leaving the agent to infer the use case from the name and context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.