What is the key difference between Ubersuggest and Crawlie?

Ubersuggest belongs to the Marketing category with cloud HTTP/SSE execution, while Crawlie belongs to the Marketing category with local stdio execution.

How do I install Ubersuggest or Crawlie in Claude Desktop or Cursor?

Copy the mcpServers JSON configuration snippet provided on this page into your claude_desktop_config.json or ~/.cursor/mcp.json file and restart your AI client.

Are Ubersuggest and Crawlie free or paid?

Ubersuggest operates under a Free / Open Source model (No auth required). Crawlie operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Ubersuggest lists 0 tools with 0 views and 0 GitHub stars. Crawlie lists 0 tools with 0 views and 97 GitHub stars.

Can I use both Ubersuggest and Crawlie together in the same MCP host?

Yes! MCP hosts like Claude Desktop, Cursor, Windsurf, Cline, and VS Code support configuring multiple servers under the mcpServers object simultaneously.

How do I install Ubersuggest or Crawlie in Claude Desktop, Cursor, or Windsurf?

Both servers follow the standard Model Context Protocol configuration format. Simply copy the JSON block from the configuration section above and paste it into your AI client's mcpServers configuration object (for instance in claude_desktop_config.json or ~/.cursor/mcp.json ), then completely restart or refresh the application.

Are Ubersuggest and Crawlie free to use, or do they require API keys?

Ubersuggest is listed under a Free / Open Source model with No auth required . Crawlie operates under a Free / Open Source model with No auth required . If environment variables are required (such as API keys), be sure to define them under the env key in your MCP client's configuration file.

Can I run both Ubersuggest and Crawlie at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both ubersuggest and crawlie as distinct keys inside the single mcpServers object in your configuration file. Your AI assistant will automatically select and call the appropriate tool from either server during chat sessions.

Which MCP server has higher directory engagement and quality ratings?

On AllMCPs, Ubersuggest has a Quality Score of 30 /100 ( Emerging ) with 0 views, 0 installs, and 0 GitHub stars. Crawlie holds a Quality Score of 41 /100 ( Fair ) with 0 views, 0 installs, and 97 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Ubersuggest vs Crawlie

In-depth architectural comparison of the Ubersuggest and Crawlie MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.

At a Glance & Executive Verdict

Ubersuggest

Marketing · Remote HTTP/SSE

Quality: 30/100 (Emerging) | Auth: No auth required

Crawlie

Marketing · Local stdio

Quality: 41/100 (Fair) | Auth: No auth required

Verdict Summary: Choose Ubersuggest if you need specialized Marketing tools running via a hosted cloud SSE transport. Choose Crawlie if your workspace requires Marketing integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.

Which MCP Server Should You Choose?

Choose Ubersuggest when:

You need dedicated capabilities in the Marketing domain.
You prefer remote streaming HTTP/SSE transport architecture.
Your security boundary fits: No auth required (Free / Open Source).

Explore Ubersuggest Details

Choose Crawlie when:

You need dedicated capabilities in the Marketing domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).

Explore Crawlie Details

Feature & Specification Comparison

Specification	U Ubersuggest Marketing	Crawlie Marketing
Summary	Ubersuggest SEO tools: keyword research, competitor analysis, backlinks, site audits and more.	Technical SEO + GEO (AI-search) site audits: hosted crawls, prioritized fixes, report diffs.
Category & Scope	Marketing	Marketing
Quality signal

Tools & Capabilities Breakdown

Ubersuggest Tools (0)

No explicit tool names declared in metadata yet. Check project README on main listing page.

Crawlie Tools (0)

No explicit tool names declared in metadata yet. Check project README on main listing page.

Ready-to-Paste Client Configurations

Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).

Ubersuggest Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "ubersuggest": {
      "url": "https://ubersuggest-mcp.neilpatelapi.com/docs"
    }
  }
}

Crawlie Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "crawlie": {
      "command": "npx",
      "args": [
        "-y",
        "-p"
      ]
    }
  }
}

Frequently Asked Questions

Ubersuggest is categorized under Marketing and uses a remote streaming HTTP/SSE transport. In contrast, Crawlie belongs to Marketing using local stdio subprocess. Select Ubersuggest when you need capabilities focused on marketing and Crawlie when you require tools for marketing.

More alternatives to Ubersuggest More alternatives to Crawlie Marketing category hub Canonical compare URL

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