Lotus — AI Citation Intelligence
Measure how AI assistants cite your brand. Returns measured data and ready-to-apply fixes.
Install
mcp_config.json
{
"mcpServers": {
"app-clicon-lotus": {
"url": "https://lotus.clicon.app/mcp/",
"type": "streamable-http"
}
}
}Documentation
Lotus — AI Citation Intelligence (MCP Server)
Lotus is a Generative Engine Optimization (GEO) platform. It measures whether your brand is actually cited as a source inside LLM-generated answers, and hands your coding agent the exact code to fix what is missing.
This repository documents the hosted Lotus MCP server. The server is a managed remote endpoint — there is nothing to install or self-host.
- Endpoint:
https://lotus.clicon.app/mcp/(trailing slash required) - Transport: streamable-http, stateless
- Registry:
app.clicon/lotus - Website: https://clicon.app
What it does
Search engines told you when you ranked badly. Generative engines do not. If an assistant hallucinates your product, ignores you, or cites a competitor instead, you lose the business with no signal that it happened.
Lotus closes that loop in three steps:
- Measure — real citation measurements across LLM answers for your domain, plus crawler activity and Search Console signals.
- Fix — prioritized "quick wins" with ready-to-install code (JSON-LD
structured data,
llms.txt). - Verify — Lotus fetches your live site and confirms the fix is really there. A fix is not "applied" because an agent said so; it is applied because it was found in production.
Tools
analyze_geo works without credentials, so any agent can evaluate a domain
before signing up. Every other tool requires an API key. Tools that take no
domain argument resolve the domain from the key itself.
Preview
| Tool | Description |
|---|---|
analyze_geo | GEO diagnosis for any domain: visibility score and estimated revenue at risk |
Read (API key)
| Tool | Description |
|---|---|
get_quick_wins | Pending fixes, each with title, category, priority, estimated impact and a hash |
get_quick_win_code | Full, install-ready code for one quick win, by hash |
get_competitor_actions | Competitor moves classified by AI-discoverability layer |
get_artifact | Retrieve a generated artifact (json_ld, llms_txt) |
get_bot_activity | AI crawler activity on your site over the last N days |
get_bleed_model | Estimated business lost through the generative channel, with its provenance |
verify_installation | Check whether your artifacts are live on your site right now |
get_citation_verdict | Latest citation score plus the per-query measurements behind it |
Write (API key)
| Tool | Description |
|---|---|
mark_applied | Marks a quick win as applied — after verifying it against your live site |
generate_share_link | Create a shareable report link |
regenerate_artifacts | Regenerate your artifacts. Rate-limited; paid tiers only |
Configuration
Add the server to any MCP-compatible client (Claude Code, Claude Desktop, Cursor, VS Code, or your own agent):
{
"mcpServers": {
"lotus": {
"url": "https://lotus.clicon.app/mcp/",
"headers": {
"X-API-Key": "YOUR_LOTUS_API_KEY"
}
}
}
}
The API key is sent as the X-API-Key header — never as a tool argument
or a query parameter. Keys are issued during onboarding at
clicon.app. Without a key the server still responds to
analyze_geo.
Exact config syntax varies slightly per client; the shape above is what most of them expect.
Usage
Talk to your agent in plain language — it picks the tools:
"Run the Lotus GEO analysis on my domain."
"Show me the pending Lotus quick wins."
"Get me the code for the highest-priority one and apply it to this repo."
"I deployed. Mark it as applied in Lotus."
On that last step Lotus fetches your live site and looks for the schema. If it is there, the fix turns green with a verification date. If it is not — because the deploy has not landed, or the snippet went in wrong — Lotus refuses to mark it. No false positives.
Lotus generates and verifies. You deploy. The server never writes to your site or your repository.
Support
Questions or access: https://clicon.app
Sourced from the repository README.
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