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MisarSEO MCP Server

run_local_nap_audit

Read-onlyIdempotent

Compare a claimed business Name/Address/Phone against listings the free OpenStreetMap business search finds near the claimed location. PARTIAL scope: checks ONE open source, not a multi-directory citation crawl (a multi-directory crawl needs licensed directory-API access this deployment does not have). A found field with no value is reported notComparable, never scored as a mismatch. overallScore on each match is a mean of comparable-field similarities (0-1), null when nothing was comparable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesClaimed business name.
phoneYesClaimed phone number, any format.
addressYesClaimed address, any format.
latitudeYes
radiusKmYesSearch radius around the claimed location, in km.
longitudeYes
projectIdYesRequired. The MisarSEO project ID to scope this call to. Get one from list_projects.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, openWorld). The description adds real behavioral context beyond them: no-value fields are reported as notComparable rather than mismatches, and overallScore is a mean of comparable-field similarities, null when nothing is comparable. It doesn't describe rate limits, pagination, or the full result shape.

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?

Four front-loaded sentences, each doing work: purpose, scope caveat, comparison semantics, score semantics. The parenthetical on licensed directory-API access is slightly verbose but justifies the PARTIAL claim rather than padding.

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?

With no output schema, the description carries the return-value burden and does explain the two most decision-relevant output concepts (notComparable handling, overallScore definition and null case). It's a seven-required-parameter, read-only tool, so the remaining gap is only the surrounding match/list structure.

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 coverage is 71%, so most parameters (projectId, radiusKm, field lengths/ranges) are documented in the schema itself. The description restates the claimed name/address/phone inputs and the 'near the claimed location' idea but adds no format, unit, or boundary guidance beyond the schema. Baseline 3 is appropriate.

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?

States a specific verb+resource: compare claimed NAP against OpenStreetMap listings near a location. It also delimits scope against the sibling search_local_businesses / directory-crawl family by explicitly naming what it is not (a multi-directory citation crawl).

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?

Clearly frames the tool's context (single open-source check with radius around a claimed location) and warns that a full multi-directory audit is out of reach in this deployment, which helps an agent avoid over-trusting results. It stops short of naming an alternative tool or the precise condition under which an agent should prefer one.

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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