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MisarSEO MCP Server

by io.github.Misar-AI
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run_brand_radar_scan

Scans real AI-answer engines and search citations for brand mentions, Share of Voice against named competitors, and cited sources. REQUIRES A PAID PLAN — a free-tier organization gets a plan-locked error, not an empty result — and CONSUMES ONE of the organization's monthly Brand Radar scan allowance PLUS one shared AI-gateway operation, both charged BEFORE the scan runs. The allowance is spent when the scan is ACCEPTED, before any answer exists — every call submits a new scan, so ask before re-running one. The scan runs on a background queue: this tool waits up to ~45 seconds for it and returns the result when it completes; if it is still running it returns the jobId instead — collect the result with get_brand_radar_scan_status (free to poll) rather than calling this tool again, which would spend another scan. Mentions and AI search volumes are nullable: a null is 'not reported by the platform', never 0.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brandYesBrand, domain, or product name to scan.
projectIdYesRequired. The MisarSEO project ID to scope this call to. Get one from list_projects.
competitorsNoUp to 5 competitor brands/domains to compare Share of Voice against.
languageCodeNoLanguage code (e.g. 'en', 'es', 'fr'). Omit it to use the project's default market language, which falls back to 'en'.
locationCodeNoDataForSEO location code. Omit it to use the project's default market, which falls back to 2840 (United States) for a project that has not set one. See dataforseo.com/help-center/locations. Some countries (e.g. Iceland, 2352) are served from Google Ads data: keyword volume/CPC/trends work, but keyword difficulty, search intent, and domain analytics are unavailable.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Goes well beyond the annotations (readOnly=false, idempotent=false) by disclosing that the allowance is charged BEFORE the scan runs and is spent on acceptance, that the call blocks ~45s before returning a jobId, and that null means 'not reported', never 0. This is exactly the cost/idempotency behavior an agent needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Long but every sentence carries load-bearing information: plan gating, cost timing, async behavior, and null semantics. The purpose is front-loaded and the warnings follow in priority order without filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

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 so: it explains the blocking-vs-jobId outcome, points to the polling tool, and clarifies null semantics. Nothing an agent needs to call and interpret this tool is missing.

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%, so the schema already documents brand, projectId, competitors, languageCode, and locationCode. The description adds no additional parameter-level syntax or semantics, so the 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+resource ('Scans real AI-answer engines and search citations for brand mentions, Share of Voice against named competitors, and cited sources') with concrete scope. It clearly differentiates from siblings by naming get_brand_radar_scan_status as the polling alternative. An agent knows exactly what this tool produces.

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?

Explicit when/when-not: requires a paid plan (free tier yields a plan-locked error, not empty), asks the agent to confirm before re-running, and directs collection of async results to get_brand_radar_scan_status instead of calling again. Alternatives and exclusions are both spelled out.

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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