Keyword research, competitor analysis, backlinks, site audits and AI search visibility — powered by Ubersuggest.
Add new capabilities to Claude beyond text generation
Example: Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example: Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
Apify
Extract data from any website with thousands of tools.
Restream
Create and manage live streams on 30+ destinations
AWS Web Search
Current, cited web results for Claude from an Amazon-operated web index, served through your own AWS account.
Craft.io
Manage your end-to-end product lifecycle - backlog, PRDs, customer feedback, roadmaps, and strategic OKRs - with Claude connected directly to your Craft.io data.
Vertiso Memory
Portable, durable memory for every AI agent you use
Metal
Strong directory entry: Ubersuggest surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Ubersuggest is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Ubersuggest is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Ubersuggest reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Ubersuggest has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, Ubersuggest benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
I recommend Ubersuggest for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Ubersuggest has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Ubersuggest is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Ubersuggest is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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Manual configuration
{
"mcpServers": {
"ubersuggest-by-neil-patel": {
"url": "https://ubersuggest-mcp.neilpatelapi.com/mcp"
}
}
}Sign in: Required.
Keyword research, competitor analysis, backlinks, site audits and AI search visibility — powered by Ubersuggest.
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
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