Babbar MCP Server

A Model Context Protocol (MCP) server that integrates with the Babbar.tech SEO API, enabling AI assistants (Claude, ChatGPT with MCP, etc.) to perform advanced SEO analysis, competitor research, backlink auditing, and content gap identification.

Features

Comprehensive SEO Analysis

• Host/Domain/URL Overview: Popularity (Value), Trust, Semantic Value, Babbar Authority Score (BAS)

• Backlink Analysis: URL, host, and domain backlink profiles

• Anchor Text Analysis: Anchor distribution and risk detection

• Page Analysis: Identify top pages by Page Value, Trust, Semantic Value, Internal Page Value

Competitor Discovery & Analysis

• Similar Hosts: Detect semantically close competitors

• Batch Analysis: Compare multiple entities (hosts/domains/URLs)

• Historical Data: Track performance over time

Advanced SEO Metrics

• Induced Strength (fi): Unique Babbar metric measuring real link value (popularity + topicality)

• Internal PageRank: Internal linking analysis

• Duplication Analysis: RollingHash (Rabin–Karp) detection of duplicate content (87%+ threshold)

Keywords & SERP Analysis

• Keyword Positions: Track Google rankings (currently supports fr_FR, en_GB, en_US, es_ES)

• SERP Data: Full SERP with features and positions

• Semantic Explorer: Related searches, People Also Ask, suggestions

Performance & Reliability

• Smart Caching: 10-day cache for heavy endpoints

• Rate Limit Management: Auto-handling + retry after 60s

• Usage Logging: Full request/response logging

• Error Handling: Clear messages for invalid key, rate limits, or API issues

Related MCP server: Semrush MCP Server

🚀 Installation & Setup

Prerequisites

• Node.js 18 or higher (check with node -v)

• npm (comes with Node.js, check with npm -v)

• Babbar API key (get it from your Babbar settings)

1. Clone the repository

git clone https://github.com/BabbarTech/BabbarMCP.git
cd BabbarMCP

2. Install dependencies

npm install

3. Set up environment variables

With Claude Desktop

Add this block to your claude_desktop_config.json:

{
  "mcpServers": {
    "babbar": {
      "command": "node",
      "args": ["/absolute/path/to/babbar-mcp/dist/index.js"],
      "env": {
        "BABBAR_API_KEY": "your_api_key_here",
        "LOG_LEVEL": "info"
      }
    }
  }
}

⚠️ Without a valid key, the server will not return real data (the API substitutes with dummy hosts/URLs).

4. Build the project

npm run build

This compiles TypeScript sources into the dist/ directory.

▶️ Usage

Local development

Run in watch mode:

npm run dev

Run built server:

node dist/index.js

🛠️ Available Tools (highlights)

Host Analysis

• babbar_host_overview → Metrics for a host

• babbar_host_backlinks_url|host|domain → Backlink analysis

• babbar_host_anchors → Anchor distribution

• babbar_host_pages_top_sv|pt|pv|iev → Top pages by different metrics

• babbar_host_similar → Competitor discovery

• babbar_host_keywords → Keywords and rankings

• babbar_host_duplicate → Duplicate content clusters

Domain Analysis

• babbar_domain_overview

• babbar_domain_backlinks_*

• babbar_domain_anchors

URL Analysis

• babbar_url_overview

• babbar_url_induced_strength (fi)

• babbar_url_semantic_similarity

• babbar_url_links_internal|external

Keyword & SERP

• babbar_keyword_serp

• babbar_semantic_questions

• babbar_semantic_related

• babbar_semantic_suggests

Advanced Analyses

• babbar_content_gap

• babbar_competitive_analysis

• babbar_anchor_profile_risk

• babbar_backlink_opportunities_spotfinder (uses Induced Strength only)

📖 Example Queries (works in French)

• Do a full metrics analysis of whisky.glass

• Give me backlink opportunities for www.recette-americaine.com

• Tell me about the semantic neighborhood of www.clubmed.fr

• Can you run a content gap analysis for whisky.glass?

• Show me the internal duplication issues within whisky.glass

• Provide me with a health analysis of whisky.glass

📊 Understanding Babbar Metrics

• Page/Host/Domain Value (0–100) → Popularity (Reasonable Surfer model)

• Page/Host/Domain Trust (0–100) → Trust score (not a direct Google authority factor)

• Semantic Value (0–100) → Popularity adjusted by topical coherence

• BAS (0–100) → Combined authority score with anti-spam (best correlated to Google rankings)

• Induced Strength (fi) → Only valid metric for backlink value, computed by Babbar API

💡 Tip: Always benchmark your metrics against your direct competitors, not the whole web.

Rate Limiting

• Each plan has a per-minute API quota.

• Remaining calls are tracked via headers (x-ratelimit-remaining).

• The MCP server auto-waits 60 seconds when the limit is exhausted.

• Errors are explicit if multiple processes compete for the limit.

Caching

• Cache enabled on POST requests (main data endpoints)

• Cache lifetime: 10 days

• Cache key = endpoint + parameters

• Reduces redundant queries and saves API credits

🐞 Error Handling

• 401 Unauthorized → Invalid or missing BABBAR_API_KEY

• 429 Too Many Requests → Rate limit exceeded, auto-retry after 60s

• 400/404/Other → Detailed error, check parameters

Logs include: endpoint, timestamp, status, and remaining quota.

📜 Logging

• Default: info level

• Levels: debug, info, warn, error

• Configure via LOG_LEVEL environment variable

• Logs include endpoint calls, rate limit status, success/failure

🛠️ Development

Run in watch mode:

npm run dev

Rebuild manually:

npm run build

Lint the code:

npm run lint

🤝 Support

• API Support: support@babbar.tech

• Docs: Babbar API Reference

• Issues: GitHub Issues

📄 License

MIT License – see LICENSE.

🙌 Contributing

Contributions are welcome!
Please open an issue first to discuss changes. Pull requests should include tests when possible.

⚡ Acknowledgments

Built with:

• Model Context Protocol SDK

• Babbar.tech API

• Node.js, TypeScript, Axios, Node-Cache, Pino