Backlink For Seo

Name: Backlink For Seo
Author: vipul510-web

@vipul510-web

About Backlink For Seo

Classic SEO suites charge heavily for link indexes. This MCP gives individuals and agencies a free, automatable path to: surface pages that mention a brand (linked or not), narrow guest-post and resource-page angles, see who links to competitors, verify whether a page links to yo

#seo #backlink #linkbuilding #mcp

Basic information

Config

No standard config provided

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Repository

Tools

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Overview

What is Backlink For Seo?

Backlink For Seo is a free, open‑source MCP server that automates SEO link research and outreach. It provides typed tools for discovering brand mentions, finding guest‑post and resource‑page opportunities, analyzing competitor backlinks, verifying on‑page links, and extracting contact signals—all orchestrated through Claude or Cursor without manual copy‑paste.

How to use Backlink For Seo?

Clone the repository, create a Python 3.10+ virtual environment, install dependencies (pip install mcp duckduckgo-search httpx beautifulsoup4 lxml), then register server.py in Claude Desktop or .cursor/mcp.json with the absolute Python path. After setup, ask the assistant to chain tools (e.g., start with find_prospects, filter by domain, run verify_page_links, then extract_contact_info).

Key features of Backlink For Seo

find_mentions: Discover pages that mention your domain (linked or unlinked).
find_prospects: Surface guest‑post, resource‑page, and roundup opportunities.
find_competitor_link_sources: Find pages linking to a competitor for outreach.
verify_page_links: Scrape a URL to confirm links and gather on‑page hints.
extract_contact_info: Pull emails, socials, and contact pages from a site.
check_page_history: Search Wayback Machine for page stability over time.

Use cases of Backlink For Seo

Brand monitoring: use find_mentions to track linked and unlinked brand mentions, then follow up accordingly.
Guest‑post research: run find_prospects by niche to identify resource pages and roundups.
Competitor backlink analysis: use find_competitor_link_sources to uncover outreach targets.
Link verification: before reaching out, confirm with verify_page_links whether a page already links to you.
Outreach preparation: chain verify_page_links and extract_contact_info to gather contact signals for finalists.

FAQ from Backlink For Seo

What data sources does Backlink For Seo use?

It pulls signals from DuckDuckGo, Wayback CDX, and direct HTTP fetches. Use judgement on rate limits, robots.txt directives, and recipient privacy (GDPR, CAN‑SPAM, etc.).

Is Backlink For Seo free?

Yes. It is a free, automatable alternative to classic SEO suites that charge heavily for link indexes.

How do I install Backlink For Seo?

Clone the repo, set up a Python 3.10+ virtual environment, install the required packages, and point your MCP client (Claude Desktop or Cursor) to server.py with the correct Python executable path.

What tools does Backlink For Seo provide?

Six tools: find_mentions, find_prospects, find_competitor_link_sources, verify_page_links, extract_contact_info, and check_page_history (Wayback checks).

Can I chain multiple tools in one workflow?

Yes. The README shows a typical workflow: start with find_prospects or find_competitor_link_sources, filter to realistic domains, run verify_page_links, then extract_contact_info before drafting outreach.