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PublicAML MCP Server

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by publicaml

List who an address transacted with

list_counterparties

Identify a wallet's counterparties and classify each as person, venue, contract, or hub. Check exposure to exchanges, mixers, or bridges, or test suspect addresses for interaction amounts.

Instructions

Who a wallet dealt with and for how much, in one of three modes:

classify — enumerate the counterparties and say what each one IS: a person, a venue (exchange/service), a hub, a deposit address, a contract or a mint/burn pseudo-address. This is the mode for 'which ordinary people funded this wallet'. An unlabelled counterparty is NOT thereby a person; that is what this mode's degree probe decides. category — did this wallet touch any exchange / mixer / gambling site / bridge at all. check — you already have suspect addresses and want to know whether this wallet dealt with them, and for how much. Addresses with no recorded interaction are simply absent from the answer.

The list is ranked and capped, so a partial answer is a floor, not the complete set, and a degree figure is a lower bound measured in a window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesWhich question you are asking. The modes do not combine.
chainNoRequired unless the address format identifies exactly one chain.
kindsNo`classify` mode: which classes to return. Default: all of them.
limitNoDefault 25.
sinceNoRestrict to a window. ISO date ('2026-06-21') or epoch seconds.
untilNo
addressYesThe wallet whose counterparties to look at.
rank_byNo'value' (default) weighs token units with no price attached, so a memecoin sender can outrank an ETH sender. Use 'tx_count' when that would mislead.
categoryNo`category` mode: the entity type to look for — cex, mixer, gambling, bridge, darknet, …
addressesNo`check` mode: the candidate counterparty addresses to test.
directionNo`classify` mode. 'in' (default) = who paid this address.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and delivers: the list is ranked and capped, a `partial` answer is a floor rather than the complete set, degree figures are lower bounds, unlabelled counterparties are explicitly NOT people, and non-interacting addresses are simply absent. These are exactly the caveats an agent needs to avoid over-reading results.

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?

Front-loaded purpose statement followed by tight mode bullets, with the capping caveat last. Every sentence earns its place, though the mode formatting is dense for a definition of this length.

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 an 11-parameter tool with no annotations and no output schema, the description covers mode selection, result capping, and interpretation caveats. It stops short of describing the shape of the returned counterparty records or how `since`/`until` windows interact with the 'lower bound' claim.

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 91%, so the schema already documents nearly every parameter, including the `rank_by` value-vs-tx_count tradeoff and the `direction` default. The description adds mode semantics and the capping caveat, which is useful but largely overlaps what the schema already supplies.

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 opening line states a specific verb and resource ('Who a wallet dealt with and for how much'), and the three named modes carve out precise sub-purposes. It never names the siblings screen_address or trace_funds, so an agent must infer the boundary from function alone rather than being told.

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?

Each mode is given an explicit question it answers, including the exact user phrasing it targets ('which ordinary people funded this wallet') and the precondition for `check` ('you already have suspect addresses'). It also rules out mode combination ('the modes do not combine').

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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