"How to obtain a diff from a GitLab repository" matching MCP servers:

Enables Claude to directly manage the Savage in a Suit website through 31 tools for pages, events, members, testimonials, podcast episodes, and site content, with all changes logged.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

An MCP server that provides AI assistants with access to the FirstPromoter affiliate management platform for managing referrals, promoters, campaigns, and commissions. It is designed for remote multi-user deployment and supports operations via HTTP/SSE transport.

MCP server that turns articles, transcripts, and markdown into LinkedIn carousel PDFs, Instagram PNGs, and Threads PNGs. Content in, slides out. No web UI, no cloud service.

A Model Context Protocol (MCP) server for Microsoft Advertising (Bing Ads / DuckDuckGo Ads). This server enables AI assistants to create, manage, and report on Microsoft Advertising campaigns programmatically.

agentcentral is a hosted MCP server for Amazon sellers that connects Claude, ChatGPT, and other AI clients to Amazon Ads, Seller Central, inventory, orders, catalog, rankings, finance, and fulfillment data. It provides fast reads from pre-materialized Amazon data, scoped API keys, OAuth-based Amazon connections, encrypted tokens, per-tenant isolation, and guarded write tools with audit log

Generates multi-platform release announcements (X, Reddit, GitHub profile, awesome-list, MCP directory) and a publish-readiness checklist for any public GitHub repository.

Enables MCP clients to pull complete Google Search Console performance data by paginating past the API's 25,000-row cap, with large results written to CSV or JSON files and only a preview returned inline. Every response includes a coverage block comparing row sums to property totals, so the model can see how much of the picture the data actually represents before making recommendations.

Enables AI assistants to check how discoverable a website is to AI search engines and assistants by inspecting signals like crawler access, llms.txt, structured data, and on-page metadata, and returning a 0-100 visibility score.

Find out how AI assistants and search engines talk about your brand. Ask how often ChatGPT, Perplexity and Google's AI answers mention you, where you rank, how positive those mentions are, which sites they cite, and how you compare with competitors. Your assistant can also set up and adjust the monitoring for you, showing a preview and asking before anything that deletes data or uses up your plan.

Model Context Protocol (MCP) server implementation for DataForSEO, enabling AI assistants to interact with selected DataForSEO APIs and obtain SEO data through a standardized interface.

GEO (Generative Engine Optimisation). This tool shows you exactly how AI search engines see your content - claim density, writing quality, E-E-A-T signals, extractability. Research-backed metrics that correlate with 40% higher AI citation rates.

Enables AI agents to read a Google Ads account, prepare and validate allowlisted changes, obtain approval, apply an unchanged batch, and read results back through a local stdio MCP server.

A joke/demo Model Context Protocol server that injects cringe-worthy advertisements into LLM responses, showcasing both how to build MCP servers and the risks of ad-injecting intermediaries.

Connects MCP clients to ThriveStack AI Visibility data, enabling users to see how AI search engines mention and cite their brand, compare with competitors, and decide what to publish next.

Lets an AI assistant check any URL to see how much of a page's main content is present in the raw HTML versus only after JavaScript runs, showing which text blocks, meta fields, canonical tags, JSON-LD and links AI crawlers like GPTBot and ClaudeBot cannot read. It also reports what robots.txt allows for 22 AI bot tokens and how the site responds to each bot's user-agent.

Enables querying competitor App Store ads from Apple's EU DSA repository, including creative copy, placements, and ad longevity, through tools like search_app_advertiser and get_competitor_ads.

Paste a URL to see exactly how it renders as a social card on Twitter, LinkedIn, Facebook, and Slack. Generate custom OG images from templates.

Enables an agent to reverse engineer how any product is distributed from a single URL, returning an evidence-cited scorecard, per-community verdicts on where promotion is allowed (channel, mine, gated, closed, unknown), and a deterministic 7/30-day plan. It also exposes the underlying evidence, content, playbooks, run comparison, and report validation as callable tools and named prompts.

Enables SEO auditing of websites from MCP-capable IDEs, providing crawler and rendered views, scoring, and ROI-ranked fix plans that agents can apply directly in the repository.

Agent-native Amazon catalog auditing tool that enables AI agents to scan, check, and diff Category Listing Reports and live Seller Central listings via MCP tools.

A remote Model Context Protocol server developed by Inxy.ai that lets any AI agent — Claude, ChatGPT, Cursor, and others — audit a website or Shopify store for AEO / GEO / LLMO readiness: how likely ChatGPT, Claude, Perplexity, and Google AI are to cite it.

Enables querying how often a brand is recommended by AI search and chat surfaces, returning recommendation and inclusion rates for any given brand.

This MCP server replicates how a creative strategist gathers context by expanding queries and performing hybrid search against a Google Drive knowledge base, delivering structured, role-categorized context for ad copy and creative briefs.

Enables tracking AI search visibility by showing how ChatGPT, Gemini, Google AI Mode, and Google AI Overviews answer your tracked questions, whether they mention your brand, how you compare with competitors, and which sources they cite.

Analyse what works → make Reels and carousels → publish or queue them → review how they did. All from a chat with Claude.

Make AIs recommend your business. Measures how AI assistants answer the questions your market asks, which sources they cite, and gives the levers to shape those answers. 43 tools on a hosted Streamable HTTP endpoint at https://mcp.epovest.com/mcp

An MCP server that lets agents collect a company's entire public marketing footprint from a single URL — paid ads, organic social, SEO, AI-crawler stance, Reddit and founder activity, tracking pixels, and funnel signals — and return a compact scorecard plus an evidence index with unknowns. It also exposes tools to pull the underlying ad copy, posts and media, retrieve the analysis playbook, diff two runs over time, and validate that a generated report's citations resolve without invented spend.

Enables analyzing a corpus of AI answers or competitor content to surface recurring character-level phrases, which brands and domains occupy those answers, and how homogenized the answer space has become. Exposes an analysis tool, a self-check that validates the measurement against control corpora, and a method/limits explainer, all read-only and working from JSON sample records.

Acts as a persistent log of ad creative reviews. Stores each review's ad name, funnel stage, score, media link, and full review text so agents can look back at how past creatives were scored.