# io.github.sharozdawa/ai-visibility (npm · ai-visibility-mcp)

Track brand visibility across ChatGPT, Perplexity, Claude, and Gemini.

- Trust score: 65/100 (medium)
- Change this week: +19
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- npm · `ai-visibility-mcp`: 65/100 (this document), [markdown](https://verifymcp.io/servers/sharozdawa-ai-visibility/ai-visibility-mcp.md), [page](https://verifymcp.io/servers/sharozdawa-ai-visibility/ai-visibility-mcp)

## Channel facts

- Registry: `npm`
- Package: `ai-visibility-mcp`
- Version: `1.0.0`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Supply Chain Security**: 86/100
  - No malware found by supply-chain analysis.
  - Only part of the dependency tree could be resolved (94 of 98), so this covers what we could see, not the whole tree.
  - No install/post-install scripts declared.
  - Only part of the dependency tree could be resolved (94 of 98), so this covers what we could see, not the whole tree.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 134 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 77/100
  - AI-judged instruction clarity (excellent).
  - Tool/resource definitions use about 415 tokens (~69/item across 6 items; 6 tools + 0 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 0/100
  - Stability not yet verified: not enough scan history yet (needs a 30-day window).
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

**Unverified: 1 category.** A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

## Install

### Claude

```bash
claude mcp add sharozdawa-ai-visibility -- npx -y ai-visibility-mcp
```

### Codex

```bash
codex mcp add sharozdawa-ai-visibility -- npx -y ai-visibility-mcp
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "sharozdawa-ai-visibility": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "ai-visibility-mcp"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add sharozdawa-ai-visibility --command npx --arg -y --arg ai-visibility-mcp
```

### Hermes

```yaml
mcp_servers:
  sharozdawa-ai-visibility:
    command: "npx"
    args: ["-y", "ai-visibility-mcp"]
```

### Other

```json
{
  "mcpServers": {
    "sharozdawa-ai-visibility": {
      "command": "npx",
      "args": [
        "-y",
        "ai-visibility-mcp"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-02 (score 65, +44)

- [security regression] Provenance: unverified → fail
- [security improvement] Install scripts: unverified → pass
- [security improvement] Known CVEs: unverified → partial
- [security improvement] Malware scan: unverified → pass
- [security] Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window).
- [functional regression] Tool coverage: 100 → unverified
- [functional improvement] Schema quality: unverified → excellent
- [functional improvement] License: unverified → pass
- [functional improvement] Dependency health: unverified → partial
- [functional improvement] Maintenance: unverified → pass
- [functional improvement] MCP protocol: unverified → pass
- [functional] First check of Schema quality: unverified
- [functional] Licence: MIT

### 2026-07-31 (score 21, −25)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-27 (score 46)

First indexed and scored.

## MCP tools (6)

### `check_brand_visibility` (~106 tokens)

Check a brand's visibility across AI platforms (ChatGPT, Perplexity, Claude, Gemini). Simulates realistic queries and analyzes mention rates, positions, sentiment, and competitor landscape.

Input parameters:

- `brand` (string, required): The brand name to check visibility for
- `keywords` (array): Industry keywords related to the brand (e.g., ['SEO', 'analytics']). Used to generate relevant queries.
- `platforms` (array): Which AI platforms to check. Defaults to all four platforms.

### `check_single_query` (~89 tokens)

Check if a brand is mentioned for a specific query on a specific AI platform. Returns mention status, position, context snippet, sentiment, and competitor mentions.

Input parameters:

- `brand` (string, required): The brand name to check
- `platform` (string, required): The AI platform to check on
- `query` (string, required): The exact query to check (e.g., 'What are the best SEO tools?')

### `get_visibility_score` (~50 tokens)

Calculate an overall AI visibility score (0-100) for a brand across all four AI platforms. Includes per-platform breakdowns and improvement recommendations.

Input parameters:

- `brand` (string, required): The brand name to score

### `compare_brands` (~69 tokens)

Compare the AI visibility of multiple brands side by side. Shows per-platform scores, overall rankings, and relative strengths.

Input parameters:

- `brands` (array, required): List of brand names to compare (2-10 brands)
- `keyword` (string): Optional industry keyword for context (e.g., 'project management')

### `get_recommendations` (~76 tokens)

Get actionable recommendations to improve a brand's AI visibility. Prioritized suggestions based on current score and industry best practices.

Input parameters:

- `brand` (string, required): The brand name to get recommendations for
- `current_score` (number): Current visibility score (0-100) if known. If not provided, a quick check will be performed.

### `list_platforms` (~25 tokens)

List all supported AI platforms with details about how each sources and presents brand information.

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/sharozdawa-ai-visibility/ai-visibility-mcp#diagnostics

## Score history

- 2026-08-03: 65
- 2026-08-02: 65
- 2026-08-01: 21
- 2026-07-31: 21
- 2026-07-30: 46
- 2026-07-28: 46
- 2026-07-27: 46

## Links

- npm package: https://www.npmjs.com/package/ai-visibility-mcp
- Socket report: https://socket.dev/npm/package/ai-visibility-mcp
- Repository: https://github.com/sharozdawa/ai-visibility
- Changelog RSS feed: https://verifymcp.io/servers/sharozdawa-ai-visibility/ai-visibility-mcp/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/sharozdawa-ai-visibility/ai-visibility-mcp/changelog.json
- HTML version of this page: https://verifymcp.io/servers/sharozdawa-ai-visibility/ai-visibility-mcp