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sebastienrousseau

structured-address-fix-mcp

by sebastienrousseau
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Python
Local

Remediate a postal address

remediate_address
Read-onlyIdempotent

Remediates postal addresses to ISO 20022 compliance by returning corrected address, findings, and patch operations with confidence scores.

Instructions

Propose the compliant form of an address, with explained changes.

Returns the findings, the before/after addresses, and the patch
operations (each carrying the finding it resolves, the source token,
and a confidence score).

Args:
    address: The postal address to remediate.
    policy_id: The policy to remediate for (defaults to cbpr-2026).
    as_of: The assessment date (YYYY-MM-DD); defaults to today.
    country_hint: Country to assume when the address has none.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_ofNoThe assessment date as an ISO 8601 string (YYYY-MM-DD). Decides cliff wording; defaults to today.
addressYesAn ISO 20022 postal address as a JSON object using canonical field names, e.g. {'street_name': 'Downing St', 'building_number': '10', 'post_code': 'SW1A 2AA', 'town_name': 'London', 'country': 'GB'} or {'address_lines': ['10 Downing St', 'London SW1A 2AA'], 'country': 'GB'}.
policy_idNoThe policy to assess against (see list_policies). Defaults to 'cbpr-2026' when omitted.
country_hintNoISO 3166-1 alpha-2 hint.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.2

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. Description adds what the tool returns (findings, before/after, patch operations) and explains parameters. No contradictions, but no additional behavioral traits beyond annotations.

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?

Description is short and front-loaded with the main purpose. The Args section is succinct. No unnecessary repetition.

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?

Output schema exists, so return values are covered. Annotations and schema provide safety context. However, usage guidance is missing, which would improve completeness.

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 100%, and the description's Args section adds informal examples (e.g., address format with street_name, building_number). This adds some value, but the schema already provides detailed descriptions for all parameters.

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?

Clearly states it proposes the compliant form of an address with explained changes. Verb+resource is specific. However, it does not differentiate from sibling tools like assess_address which might also check compliance.

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 on when to use this tool versus alternatives like assess_address or classify_address. The description only explains parameters, not usage context.

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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