RankControl vs AI Visibility

A side-by-side look at the RankControl and AI Visibility MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

RankControl logoRankControlMarketing · Local subprocess (stdio)Connect your RankControl workspace to Claude, Cursor or any MCP client. Plan and publish articles, find backlink prospects and draft outreach, and check Google and Bing rankings plus citations in six AI engines.56GoodAuth: oauth 2.0AI Visibility logoAI VisibilityMarketing · Local subprocess (stdio)Track brand visibility across ChatGPT, Perplexity, Claude, and Gemini. Visibility scores, sentiment analysis, competitor detection, and trend charts.59GoodAuth: not declared

Verdict: choose RankControl for marketing work as a local process; choose AI Visibility for marketing as a local process. You can also run both side by side in one mcpServers block.

Which MCP server should you choose?

RankControl logoChoose RankControl when

  • You need dedicated capabilities in the Marketing domain.
  • You prefer a local stdio subprocess transport.
  • Its auth model fits you: OAuth 2.0.
Explore RankControl

AI Visibility logoChoose AI Visibility when

  • You need dedicated capabilities in the Marketing domain.
  • You prefer a local stdio subprocess transport.
  • You want tools like check_brand_visibility, check_single_query, get_visibility_score.
Explore AI Visibility

Feature & specification comparison

Rows where the two servers differ are marked.

SpecRankControl logoRankControlAI Visibility logoAI Visibility
CategoryMarketingMarketing
Quality signal56/100 · Good59/100 · Good
Install commandConfirmedConfirmed
TransportLocal subprocess (stdio)Local subprocess (stdio)
AuthOAuth 2.0Not declared
PricingPaid serviceNot declared
Required env varsNone listedNone listed
Verified ownerCommunity listingCommunity listing
GitHub stars511
Directory activity 3 views 0 installs 0 upvotes 3 views 0 installs 0 upvotes
ToolsNot listed6

Tools & capabilities

RankControl tools

No tool names declared yet. Check the project README from the listing page.

AI Visibility tools 6

  • check_brand_visibilityCheck a brand's visibility across AI platforms (ChatGPT, Perplexity, Claude, Gemini). Simulates realistic queries and analyzes mention rates, positions, sentiment, and competitor landscape.
  • check_single_queryCheck if a brand is mentioned for a specific query on a specific AI platform. Returns mention status, position, context snippet, sentiment, and competitor mentions.
  • get_visibility_scoreCalculate an overall AI visibility score (0-100) for a brand across all four AI platforms. Includes per-platform breakdowns and improvement recommendations.
  • compare_brandsCompare the AI visibility of multiple brands side by side. Shows per-platform scores, overall rankings, and relative strengths.
  • get_recommendationsGet actionable recommendations to improve a brand's AI visibility. Prioritized suggestions based on current score and industry best practices.
  • list_platformsList all supported AI platforms with details about how each sources and presents brand information.

Ready-to-paste client configs

Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.

RankControl

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "rankcontrol": {
      "command": "npx",
      "args": [
        "-y",
        "rankcontrol"
      ]
    }
  }
}

AI Visibility

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "sharozdawa-ai-visibility": {
      "command": "npx",
      "args": [
        "-y",
        "ai-visibility-mcp"
      ]
    }
  }
}

Frequently asked questions

RankControl is categorized under Marketing and uses a local stdio subprocess. AI Visibility belongs to Marketing and uses a local stdio subprocess. Pick RankControl for marketing work and AI Visibility for marketing.

Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.

RankControl is listed as a paid service. Auth: oauth 2.0. AI Visibility has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.

Yes. MCP clients support multiple servers: add rankcontrol and sharozdawa-ai-visibility as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, RankControl has a quality signal of 56/100 (Good) with 3 views, 0 installs and 5 GitHub stars. AI Visibility has 59/100 (Good) with 3 views, 0 installs and 11 GitHub stars.