Mcp Geo

DigestSEO — AI Visibility MCP for SEO & GEO

[](https://github.com/AKzar1el/mcp-geo/actions/workflows/ci.yml) [](https://www.npmjs.com/package/digestseo-mcp) [](https://registry.modelcontextprotocol.io/v0/servers?search=io.github.AKzar1el/digestseo-mcp) [](./LICENSE) [](https://www.typescriptlang.org/) [](https://workers.cloudflare.com/) [](https://modelcontextprotocol.io/) [](https://github.com/AKzar1el/mcp-geo/stargazers)

Quick Install

Runs locally over stdio with your own API keys — all data stays on your machine (see [Privacy Policy](#privacy-policy)). Set at least one engine key (OPENAI_API_KEY, ANTHROPIC_API_KEY, GEMINI_API_KEY, PERPLEXITY_API_KEY, SERPAPI_API_KEY); engines without a key skip gracefully.

Claude Desktop / any MCP client (npx):

{
  "mcpServers": {
    "digestseo": {
      "command": "npx",
      "args": ["-y", "digestseo-mcp"],
      "env": {
        "OPENAI_API_KEY": "sk-...",
        "GEMINI_API_KEY": "your_key_here"
      }
    }
  }
}

Claude Code:

claude mcp add --transport stdio digestseo -s user --env GEMINI_API_KEY=your_key_here -- npx -y digestseo-mcp

Cursor:

[](https://cursor.com/en/install-mcp?name=digestseo&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsImRpZ2VzdHNlby1tY3AiXSwiZW52Ijp7Ik9QRU5BSV9BUElfS0VZIjoiIiwiQU5USFJPUElDX0FQSV9LRVkiOiIiLCJHRU1JTklfQVBJX0tFWSI6IiIsIlBFUlBMRVhJVFlfQVBJX0tFWSI6IiIsIlNFUlBBUElfQVBJX0tFWSI6IiJ9fQ%3D%3D)

Claude Desktop extension (one-click): download the .mcpb bundle from the latest release and double-click it — Claude Desktop prompts for the API keys.

First run: ask your client to "track acme.com as brand acme, then refresh it" — track_brand creates the brand with generated prompts, refresh_brand runs the first scan, check_visibility shows the scores.

AI agents installing this server: follow [llms-install.md](./llms-install.md). Prefer a remote server with cron auto-refresh? Self-host on Cloudflare Workers below.

---

mcp-geo is an open-source AI visibility tracker that measures how often your brand is cited by ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. It's the GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) equivalent of Google Search Console — built as an MCP server so you can query your AI visibility data directly inside Claude.ai, Claude Desktop, Claude Code, Cursor, Codex CLI, or any MCP-compatible client.

> Prefer zero setup? Try the hosted version at digestseo.com — managed Cloudflare infra, no API keys to manage, multi-brand, scheduled refresh, web UI. Waitlist now open. Join waitlist →

---

What it produces

Connect via MCP, ask Claude "Run an AI visibility analysis on [my brand]", and within 90 seconds you get a strategist-quality memo grounded in real per-engine data:

[](docs/demo-report-full.png)

[View the full report including content gaps, engine recommendations, and synthesis →](docs/demo-report-full.png)

The report above was generated by Claude through the digestseo-mcp MCP server. The conversation chained five tools — check_visibility, compare_competitors, get_citations (Perplexity + Claude), and get_content_gaps — to produce a 4-engine analysis with citation excerpts and a 3-recommendation strategy memo.

---

What's New

[0.3.0] — July 2026

• Local stdio CLI on npm (npx -y digestseo-mcp): the same MCP tools backed by a local SQLite database (~/.digestseo/digestseo.sqlite) — no Cloudflare account needed. Engines run inline with your own API keys.
• Local brand-management tools (CLI only): track_brand, list_brands, generate_prompts. Workers deployments keep these behind the X-Seed-Secret-gated /admin/* routes.
• Runtime-agnostic core (src/core/) shared by the Worker and the CLI, with a Db contract implemented by D1 and better-sqlite3 adapters. All 0.2.1 accuracy and security fixes carry over to both runtimes.
• Distribution metadata: official MCP Registry server.json, MCPB desktop extension (.mcpb bundle), Dockerfile, llms-install.md for AI agents, release-publish workflow.

[0.2.1] — June 2026

• Optional CONNECT_SECRET gate on the OAuth flow. By default the OSS build auto-completes /authorize for any MCP client that knows your worker URL — anyone who finds the URL can connect and call refresh_brand, spending your engine API credits. Set CONNECT_SECRET and the browser step of the connect flow now asks for it before issuing a token. See [SECURITY.md](./SECURITY.md).
• Accurate citation matching. Brand/competitor mentions now require word boundaries (acme no longer matches "acmeshop"), and linked-citation checks require the exact domain or a subdomain (notacme.com no longer counts as a link to acme.com).
• Per-brand aliases and exclude_terms. Aliases always count as a mention; exclude terms suppress the bare-word match on the brand name and domain root — so "Monday" the brand stops matching "monday" the weekday, while monday.com still counts. Apply migrations/0005_brand_alias_exclude.sql; existing brands behave exactly as before.
• get_visibility_history consistency. Partially-finished runs now count toward history (matching check_visibility's 0.2.0 behavior), and fully-failed runs no longer show up as fake zero scores.
• CI + unit tests. GitHub Actions runs tsc --noEmit plus a pure-function unit suite (npm run test:unit) covering mention matching, citation extraction, and score aggregation on every push.
• Docs now recommend OpenAI + Anthropic as the starting engine pair — the Gemini free tier rate-limits brands with more than ~5 prompts and produced misleading first-run data as the documented cheapest path.
• Constant-time comparison for SEED_SECRET / CONNECT_SECRET.

[0.2.0] — May 2026

• Per-engine HTTP fan-out. /admin/run-live now creates one runs row per engine and self-fetches /admin/run-engine once per engine. Each engine runs in its own worker invocation with its own free-plan 50-subrequest budget — a single-invocation fan-out used to burst past the cap mid-run and lose half the rows.
• Service binding (env.SELF) dispatches the per-engine fan-out through Cloudflare's internal fabric instead of a public-URL fetch, dodging the "Worker called itself" guard (error 1042) that silently blocks the latter.
• Status column on prompt_responses (ok / failed / skipped) plus error_message. Failed engine calls used to write raw_response='ERROR: ...' rows that downstream scoring treated as real zero-mention hits; now they're explicitly excluded.
• FK-resistant inserts. /admin/run-engine INSERT OR IGNOREs its runs row before persisting — D1 is eventually consistent across edge regions, and the upstream INSERT INTO runs from /admin/run-live doesn't always replicate before the downstream engine call lands. The IGNORE makes the FK happy either way.
• Bulk D1 batch. Each engine collects its 20 prompt results in memory then flushes inserts + cache writes + the final UPDATE runs SET status='completed' in a single D1.batch() call. Drops the per-invocation subrequest count from ~89 to ~26.
• Relaxed visibility queries. getLatestCompletedRun anchors on EXISTS(ok rows) instead of status='completed', so partially-finished runs still surface their data in MCP tool output instead of silently disappearing.
• New admin route POST /admin/cleanup-failed-runs for one-shot deletion of legacy polluted rows after migrating to 0004.

[0.1.1] — May 2026

• Manual install is now the canonical path. The unreliable bash setup script was removed; SETUP.md is self-contained and copy-pasteable, with every interactive wrangler prompt documented inline.

[0.1.0] — May 2026

• Initial public release.
• 5-engine support: ChatGPT (gpt-4o-mini), Claude (claude-haiku-4-5), Perplexity (sonar), Gemini (gemini-2.5-flash-lite), and Google AI Overviews (via SerpAPI).
• 6 MCP tools: check_visibility, get_visibility_history, compare_competitors, get_citations, get_content_gaps, refresh_brand.
• Engines are opt-in based on which API keys you provide — set only the credentials you have, the rest skip gracefully.
• Cloudflare Cron Trigger that auto-refreshes tracked brands every 6h, respecting per-brand refresh_frequency (daily/weekly).
• D1-backed storage for brands, prompts, runs, citations, and a shared prompt cache.

---

What Can This Do?

• See which AI tools cite your brand and which don't — get a per-engine breakdown of who's citing you for buyer-intent queries.
• Track AI visibility weekly, automatically — the built-in Cron Trigger re-runs scans on the cadence you configure per brand.
• Compare your AI visibility to competitors — share-of-voice percentages, prompts you win, prompts they win.
• Find content gaps — Claude-Haiku-synthesized recommendations grounded in your actual losing prompts.
• Use it inside Claude.ai conversations — add the deployed Worker URL as a custom MCP connector and ask in natural language.
• Self-hosted on your own Cloudflare account — your API keys, your data, your cost ceiling. The free Workers + D1 tiers cover a single brand with daily refreshes.

See [the example report above](#what-it-produces) for what this looks like in practice.

---

Available Tools

| Tool | What it does | What you provide | |---|---|---| | check_visibility | Latest AI visibility snapshot across all configured engines for a tracked brand, with per-engine scores, winning prompts, and losing prompts. | brand_id, optional engines[] filter | | get_visibility_history | Time-series history of overall and per-engine visibility, bucketed daily or weekly. | brand_id, optional days (default 30), optional granularity (daily/weekly) | | compare_competitors | Share-of-voice comparison against competitor domains, with prompts you win and prompts they win. | brand_id, optional competitor_domains[], optional days | | get_citations | The actual citation events — prompt, engine, response excerpt, citation type, brand URL when present. | brand_id, optional days, optional engine filter | | get_content_gaps | Prioritized Claude-Haiku-generated content recommendations targeting your losing prompts. | brand_id, optional max_recommendations (1-10) | | refresh_brand | Manually trigger a fresh scan across every engine whose API key is set. | brand_id, optional engines[] filter |

The local stdio CLI (npx, desktop extension, Docker) additionally provides brand management — on a Workers deployment the same operations live behind the X-Seed-Secret-gated /admin/* routes instead:

| Tool (local CLI only) | What it does | What you provide | |---|---|---| | track_brand | Start tracking a brand: creates it locally and generates its buyer-intent prompt set (Claude Haiku when ANTHROPIC_API_KEY is set, three starter prompts otherwise). | brand_id, name, domain, optional category, competitors[], aliases[], exclude_terms[], prompt_count | | list_brands | List tracked brands with domains, competitors, and active prompt counts. | — | | generate_prompts | Regenerate a brand's prompt set via Claude Haiku (replaces active prompts, keeps history). | brand_id, optional count (default 20) |

---

Getting Started

Step 1 — Get API keys

Engines are opt-in. Pick the ones you want; the rest skip silently.

• OpenAI — ChatGPT engine. ~€0.0004 per prompt with gpt-4o-mini. Batch path roughly halves that. platform.openai.com
• Anthropic — Claude engine, plus prompt generation and content-gap analysis (both call Claude Haiku). ~€0.0002 per prompt. Free trial credits are usually enough to evaluate. console.anthropic.com
• Google AI Studio (Gemini) — Gemini engine. ~€0.0001 per prompt. The free tier has a low per-minute cap, so brands with more than ~5 prompts hit HTTP 429 and drop out of scoring (see [Troubleshooting](#troubleshooting)) — treat it as an opt-in add-on, not a starting engine. aistudio.google.com
• Perplexity — Perplexity Sonar engine. ~€0.005-0.008 per prompt. Paid only. perplexity.ai/settings/api
• SerpAPI — Google AI Overviews engine. ~€0.005 (free tier) / ~€0.0015 (volume) per prompt. Free tier covers ~100 calls/month — enough for development. serpapi.com/dashboard

Recommended starting pair: OpenAI + Anthropic (Claude). Both bill per token with no rate-limit surprises, so your first scan returns clean, scorable data across the ChatGPT and Claude engines — and the Anthropic key also powers prompt generation and content-gap analysis. Solo evaluation runs comfortably under €1/month on the two together. Add Gemini, Perplexity, or SerpAPI deliberately once you want more coverage; Gemini's free tier rate-limits and Google AI Overviews often returns no result (scored as a zero), so leading with the cheapest path can skew your first run.

Step 2 — Deploy to your Cloudflare account

The deploy is 6 commands and takes about 5 minutes. See [SETUP.md](./SETUP.md) for the full walkthrough with explanations and troubleshooting, or follow the quick version below.

# 1. Install deps
npm install

# 2. Log in to Cloudflare
npx wrangler login

# 3. Copy the config template
cp wrangler.example.jsonc wrangler.jsonc

# 4. Create KV namespace + D1 database, paste each printed id into wrangler.jsonc
npx wrangler kv namespace create OAUTH_KV
npx wrangler d1 create digestseo-db

# 5. Set the required secret + at least one engine API key
#    Recommended starting pair — both bill per token, clean first-run data:
npx wrangler secret put SEED_SECRET
npx wrangler secret put CONNECT_SECRET      # recommended — gates who can connect (see SECURITY.md)
npx wrangler secret put OPENAI_API_KEY      # ChatGPT engine
npx wrangler secret put ANTHROPIC_API_KEY   # Claude engine + prompt generation

# 6. Apply migrations and deploy
npx wrangler d1 migrations apply digestseo-db --remote
npx wrangler deploy

After deploy, wrangler prints your Worker URL. Save it.

Step 3 — Connect to your MCP client

After wrangler deploy finishes, you get a URL like https://digestseo-mcp.YOUR-SUBDOMAIN.workers.dev.

Claude.ai (web)

Settings → Connectors → Add custom connector. Paste:

https://YOUR-WORKER-NAME.YOUR-SUBDOMAIN.workers.dev/mcp

Complete the OAuth handshake. The connector turns green when ready.

Claude Code

claude mcp add --transport http digestseo https://YOUR-WORKER-NAME.YOUR-SUBDOMAIN.workers.dev/mcp

Then run /mcp inside Claude Code to complete the OAuth handshake in your browser.

Claude Desktop

Edit your Claude Desktop config:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "digestseo": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://YOUR-WORKER-NAME.YOUR-SUBDOMAIN.workers.dev/mcp"
      ]
    }
  }
}

Restart Claude Desktop after editing.

Cursor

Edit ~/.cursor/mcp.json:

{
  "mcpServers": {
    "digestseo": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://YOUR-WORKER-NAME.YOUR-SUBDOMAIN.workers.dev/mcp"
      ]
    }
  }
}

Restart Cursor.

Codex CLI

Add to ~/.codex/config.toml:

[mcp_servers.digestseo]
command = "npx"
args = [
  "-y",
  "mcp-remote",
  "https://YOUR-WORKER-NAME.YOUR-SUBDOMAIN.workers.dev/mcp",
]

---

Environment Variables Reference

| Variable | Required | Default | Description |

…

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: AKzar1el
• Source: AKzar1el/mcp-geo
• License: MIT
• Homepage: https://digestseo.com

Install and usage instructions live in the source repository linked above.