MCP server
MCP server
Connect AI assistants like Claude, and other MCP-compatible tools directly to your LLMLab data. Ask your AI assistant about your brand’s AI visibility and get answers from your actual LLMLab data.
Connect AI assistants like Claude, and other MCP-compatible tools directly to your LLMLab data. Ask your AI assistant about your brand’s AI visibility and get answers from your actual LLMLab data.
How to Connect the LLMLab MCP Server
How to Connect the LLMLab MCP Server
1
Connect
Add the LLMLab MCP server URL to your Claude client.
https://llmlab-mcp.craveo.in/mcp
https://llmlab-mcp.craveo.in/mcp
2
Authenticate
Sign in with your LLMLab account via OAuth when prompted
Sign in with your LLMLab account via OAuth when prompted
3
Run a prompt
Ask Claude about your AI visibility data in natural language
Ask Claude about your AI visibility data in natural language
“How has our brand visibility changed over the last 2 weeks?”
“Which competitors have the highest visibility in Claude?”
“What are our most cited URLs?”
What you can do with LLMLab MCP Server
What you can do with LLMLab MCP Server
Check brand visibility across Claude, ChatGPT and Google AI Overviews.
Compare competitor performance across key metrics such as visibility, sentiment, share of voice, and position.
Analyze cited sources to see which domains and URLs AI models retrieve and cite most often, and how those sources shape your content strategy.
Inspect source content by pulling the scraped markdown of any cited URL to see exactly what an AI engine read.
Spot visibility trends by date, AI model, topic, or country to surface patterns, gaps, and opportunities to act on.
Inspect AI bot traffic from Agent Analytics. See which bots LLMLab tracks and aggregate visit counts from your access logs, grouped by bot, response status, host, path, or time bucket.
Get ranked next steps from LLMLab Actions: opportunity-scored recommendations grouped by owned pages, editorial coverage, reference sites, and UGC communities.
Run ready-made workflows with built-in prompts like weekly pulse, engine scorecard, topic heatmap, and campaign tracker. One slash command, full report.
Manage project setup by asking the assistant to create, edit, or delete prompts, topics, tags, tracked brands, and custom domain/URL classifications. Works one at a time or in batches of up to 50. LLMLab always confirms before applying a change.
Refine your brand profile so AI-generated prompt suggestions match how you actually describe your business.
Check brand visibility across Claude, ChatGPT and Google AI Overviews.
Compare competitor performance across key metrics such as visibility, sentiment, share of voice, and position.
Analyze cited sources to see which domains and URLs AI models retrieve and cite most often, and how those sources shape your content strategy.
Inspect source content by pulling the scraped markdown of any cited URL to see exactly what an AI engine read.
Spot visibility trends by date, AI model, topic, or country to surface patterns, gaps, and opportunities to act on.
Inspect AI bot traffic from Agent Analytics. See which bots LLMLab tracks and aggregate visit counts from your access logs, grouped by bot, response status, host, path, or time bucket.
Get ranked next steps from LLMLab Actions: opportunity-scored recommendations grouped by owned pages, editorial coverage, reference sites, and UGC communities.
Run ready-made workflows with built-in prompts like weekly pulse, engine scorecard, topic heatmap, and campaign tracker. One slash command, full report.
Manage project setup by asking the assistant to create, edit, or delete prompts, topics, tags, tracked brands, and custom domain/URL classifications. Works one at a time or in batches of up to 50. LLMLab always confirms before applying a change.
Refine your brand profile so AI-generated prompt suggestions match how you actually describe your business.