agentaeo-mcp-server

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github.com/agentaeoBusiness & Marketing0Updated 25w ago

About agentaeo-mcp-server

AgentAEO MCP Server audits how often brands are cited in AI-generated answers, for marketing teams and agencies assessing visibility. It tests buyer queries across ChatGPT, Perplexity, Claude, and Google AI, and returns competitor citations, estimated revenue leakage, and suggested fixes.

Key features

01Test queries across four AI engines
02Measure citation rates by query
03Identify cited competitors
04Estimate monthly revenue leakage
05Generate schema fixes and llms.txt

Use cases

01Compare competitor visibility for buyer queries
02Check a brand’s citation health
03Prioritize fixes for an AEO audit
04Assess citation gaps across client domains

MCP support

Exposes AgentAEO audits and related results to MCP-compatible agents, which can run queries and return citation data, revenue estimates, and suggested fixes.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config

{
  "mcpServers": {
    "digitaldatadriven-agentaeo": {
      "command": "npx",
      "args": [
        "-y",
        "@agentaeo/mcp-server"
      ]
    }
  }
}

Run commandnpx -y @agentaeo/mcp-server

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages

npm@agentaeo/mcp-server0.1.8stdio

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

AgentAEO MCP Server

Ask Claude: "Why is [competitor] being cited instead of us for [category] queries?" Get the answer. Get the fix.

AgentAEO is a retrieval intelligence layer for AI agents. It tells Claude, Cursor, and any MCP-compatible agent which brands are winning AI citations and exactly why.

Install in 2 minutes

npx @agentaeo/mcp-server@latest

Then in Claude Desktop, ask:

"Run an AI citation audit on [domain.com] for [category] queries. Tell me which competitors are being cited instead and why."

That is it. You now have live selection intelligence inside your AI workflow.

What this measures

AgentAEO runs real buyer queries across ChatGPT, Perplexity, Claude, and Google AI and returns:

Citation rates per engine per query
Which competitor wins each query
Revenue leakage estimate ($/month)
Exact structural reasons AI skips you
Copy-paste schema fixes

Why this exists

60% of brands investing in SEO are invisible in AI-generated answers despite strong Google rankings.

This is the Selection Gap: AI finds your brand but does not consistently choose it. Competitors enter the consideration set before you do.

AgentAEO measures this gap. Quantifies it in dollars. Generates the fix.

Also known as: Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), AI SEO — AgentAEO measures the citation layer that determines whether AI recommends you or your competitor.

How AgentAEO differs from other AEO tools

Capability	AgentAEO	Conductor	Profound	AthenaHQ	seoClarity
Live citation testing across 4 engines	✅	❌	❌	❌	❌
Revenue-at-risk estimate	✅	❌	❌	❌	❌
30-day fix blueprint	✅	❌	❌	❌	❌
Deploy-ready JSON-LD schema	✅	❌	❌	Partial	❌
llms.txt generation	✅	❌	❌	❌	❌
Free tier	✅	❌	❌	❌	❌
One-time diagnostic (no subscription)	✅	❌	❌	❌	❌
MCP server on Anthropic registry	✅	✅	✅	❌	✅

Three workflows to try now

1. Competitive intelligence

"Audit stripe.com for payment processing queries. Which fintech brands are being recommended instead of Stripe by ChatGPT and Perplexity?"

2. Own brand monitoring

"Run a citation health check on [your-domain.com] and give me the monthly revenue leakage estimate plus the top 3 fixes."

3. Agency research

"Audit these 5 domains: [list]. Rank them by Retrieval Marketing Score. Which has the biggest citation gap versus its competitors?"

Run a complete AEO audit and fix plan in 30 minutes

With AgentAEO MCP inside Claude Desktop or Claude Cowork, what used to take 30 days of manual AEO work runs in 30 minutes:

Ask Claude:

"Run a complete AEO audit on [domain.com]. Test buyer queries across all 4 engines, identify citation gaps, generate the 30-day fix blueprint, create the JSON-LD schema files, write the llms.txt, and give me a board-level summary of revenue at risk."

Output in one session:

Citation grade per engine per query
Revenue leakage estimate
Prioritised 30-day fix plan
Copy-paste JSON-LD (FAQPage, HowTo, Organization)
llms.txt file ready to publish
Executive summary for stakeholders

Built on the Retrieval Marketing Framework™

The only AEO platform with a working MCP server on the official Anthropic registry. AAA rated on Glama.

→ agentaeo.com
→ retrieval.marketing
→ @agentaeo/mcp-server on npm

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