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DigestSEO mcp Geo — AI Visibility MCP Server

Tracks brand visibility, citations, competitors, history, and content gaps across configured AI search engines.

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Install DigestSEO mcp Geo — AI Visibility MCP Server

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "digestseo-mcp-geo-ai-visibility-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@digestseo/mcp-geo"
      ],
      "env": {
        "OPENAI_API_KEY": "YOUR_VALUE_HERE",
        "ANTHROPIC_API_KEY": "YOUR_VALUE_HERE",
        "GEMINI_API_KEY": "YOUR_VALUE_HERE",
        "PERPLEXITY_API_KEY": "YOUR_VALUE_HERE",
        "XAI_API_KEY": "YOUR_VALUE_HERE",
        "SERPAPI_API_KEY": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Automated check passed— started and listed 12 tools correctly ().

Overview

DigestSEO mcp-geo — AI Visibility MCP Server gives MCP-compatible agents tools for measuring how often a tracked brand appears in AI search results. It reads locally stored brand data and scan history, while sending scan prompts to the AI providers whose API keys are configured. Use it to inspect visibility snapshots, compare competitors, review citation evidence, identify content gaps, or start a fresh scan. The package runs locally over stdio and requires Node.js 22.13 or newer.

Use cases

  • Measure a brand's latest AI search visibility
  • Compare share of voice with competitor domains
  • Review the prompts and responses producing citations
  • Find content opportunities for losing prompts
  • Refresh visibility data across configured engines

Key features

  • Cross-engine visibility snapshots
  • Daily and weekly visibility history
  • Competitor share-of-voice comparisons
  • Citation events with response excerpts
  • Claude Haiku content-gap recommendations
  • Manual multi-engine refreshes

Tools12

What DigestSEO mcp Geo — AI Visibility MCP Server lets your agent do. Expand a tool for its parameters.

Verified live~2.2k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked

Recent health check succeeded.

21/22 checks healthy over the last 95d

What it can do

From the 12 tools this server returned when we ran it; 12 declare their own safety hints.

Can delete or modify data · 2Handles credentials · 1Makes network requests · 5Read-only tools · 10
Network at startup3 connections
Files written at startup3
Install scriptsNone
npm provenanceSigned build
Package age108 days
Maintainers1

Observed 2026-11-13 in an isolated sandbox. A description of reach, not a security audit.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 7d ago via OSV.dev · @digestseo/mcp-geo (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars40Stargazers on the source repository.
npm downloads2.6kPackage downloads in the last 30 days.
Last commit2d agoMost recent push to the default branch.
Availability100%Our rolling endpoint + install checks that succeeded.
Install checkPassedOur sandbox started it and listed its tools.
Tools exposed12Callable tools this server registers over MCP.
Directory activity6 viewsConfig copies, upvotes, and views on AllMCPs.

How DigestSEO mcp Geo — AI Visibility MCP Server works

What DigestSEO mcp-geo — AI Visibility MCP Server does

DigestSEO mcp-geo — AI Visibility MCP Server exposes brand visibility analysis through MCP tools. It tracks results across configured AI search engines and returns both aggregate metrics and underlying evidence. The server can report a latest visibility snapshot, show changes over time, compare a brand with competitor domains, and list the prompts where each site wins or loses.

Its citation view provides the prompt, search engine, response excerpt, citation type, and brand URL when one appears in the response. A separate content-gap tool turns losing prompts into prioritized recommendations generated with Claude Haiku. The refresh operation starts a new scan for every engine with an available API key.

How it works

The package runs as a local stdio MCP process. An MCP client launches it with npx -y @digestseo/mcp-geo, then exposes its tools to an assistant. Brands, scan history, and cached responses remain on the local machine. Scan prompts are sent to the AI providers selected through environment variables, and engines without credentials are skipped.

Visibility history can be grouped by day or week and includes overall and per-engine results. Competitor comparisons report share of voice along with prompts won by the tracked brand and by competing domains. Fresh scans may incur charges from the configured AI providers.

Setup and configuration

Node.js 22.13 or later is required. At least one provider key should be available for engine-backed scans; credentials can be supplied in the MCP client's environment configuration:

  • OPENAI_API_KEY
  • ANTHROPIC_API_KEY
  • GEMINI_API_KEY
  • PERPLEXITY_API_KEY
  • XAI_API_KEY
  • SERPAPI_API_KEY

Provider keys are not needed merely to discover the MCP tools. A minimal local configuration uses the package command as the server command and passes selected keys through the client's environment settings. Claude Desktop can launch the package directly, while Claude Code and Codex CLI provide corresponding MCP add commands. The project also documents remote Worker deployment for clients that require an HTTPS MCP endpoint.

Tools and capabilities

  • visibility.check returns the latest overall snapshot, per-engine scores, and prompts that produced wins or losses.
  • visibility.history provides daily or weekly time-series data for overall and engine-specific visibility.
  • visibility.compare measures share of voice against competitor domains and identifies winning prompts for both sides.
  • visibility.citations exposes citation records with response excerpts, citation types, and brand URLs when present.
  • visibility.content_gaps produces prioritized recommendations for losing prompts using Claude Haiku.
  • visibility.refresh launches a new scan across engines whose credentials are configured.

Limitations and notes

Only engines with configured API keys participate in refresh operations. The local package is a stdio server; clients that cannot launch local MCP processes need a self-hosted remote deployment. The public remote endpoint is not a no-key service for fresh scans. Provider usage can create external charges, and scan prompts are transmitted to the providers selected in the environment.

Read the full README View source on GitHub

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Frequently Asked Questions about DigestSEO mcp Geo — AI Visibility MCP Server

DigestSEO mcp-geo — AI Visibility MCP Server is an MCP server that connects AI agents to configured AI search providers and exposes tools for visibility checks, history, competitor comparisons, citation records, content gaps, and scan refreshes. It runs locally over stdio and uses provider API keys supplied through the environment.

Install it by configuring your MCP client to launch `npx -y @digestseo/mcp-geo`. Node.js 22.13 or newer is required. Add the provider API keys you want the process to use; tool discovery works without provider keys.

It supports `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, `GEMINI_API_KEY`, `PERPLEXITY_API_KEY`, `XAI_API_KEY`, and `SERPAPI_API_KEY`. Engines without a configured key are skipped during refreshes, and at least one key is needed for engine-backed scanning.

Yes, it works with Claude Desktop through a local stdio configuration. Set the server command to `npx`, pass `-y` and `@digestseo/mcp-geo` as arguments, and place selected provider keys in the server environment.

It stores brands, scan history, and cached responses on the local machine running the server. Scan prompts are sent to the AI providers whose API keys are configured.

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