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Freedom251 › Blog › AI directories

A Searchable Directory for AI Tools, MCP Servers, Skills and Prompts

By Freedom251 Team · · 3 min read

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AIMarketly is Muhammad Adnan’s searchable directory for AI tools, AI skills, MCP servers, prompts and related developer, automation and productivity resources. Adnan’s stated goal is to “Make it easier to discover and compare useful AI resources without searching through dozens of different websites.” Its 40K+ headline is a project scale claim, not an independently verified count.

What is AIMarketly?

In his September 29, 2026 DEV Community introduction, full-stack engineer and IslamiCloud founder Muhammad Adnan presents AIMarketly as a directory for finding AI and developer resources. His premise is that “the problem isn’t finding an AI tool anymore — it’s finding the right one.” As the number of tools and categories grows, he argues, finding a suitable resource can become difficult, and directories themselves can be hard to navigate.

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The project is intended to bring discovery and comparison into one place. That is Adnan’s stated purpose, not a measured claim that the directory has already made discovery faster or easier for its users.

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What kinds of resources does it cover?

Adnan describes the directory as covering AI tools, AI skills, MCP servers, prompts, developer tools, and automation and productivity resources. The article gives examples of the kinds of listings and use cases the directory aims to organize:

  • For developers: AI coding tools, developer assistants, APIs, AI frameworks, MCP servers and code-review tools.
  • For marketing work: content and SEO tools, social media resources, image and video generation, and marketing automation.
  • Across AI workflows: skills and prompts, alongside other productivity and automation resources.

These examples describe the author’s intended categories; the article does not independently verify every category’s current inventory.

What does “40K+” mean?

The article’s headline uses “40K+” as a scale claim. A search-result listing associated with it gave project counts of 21,000+ AI tools, 11,000+ AI skills, 12,000+ MCP servers and 2,000+ prompts, alongside a total of 40,000+ AI resources. Those are figures attributed to the project, not an independent audit. The opened article body does not display the category totals, and it supplies no counting method or verification details; treat the figures as author-reported rather than confirmed live inventory.

What can users do, and what is still a goal?

Adnan describes searchable discovery and category browsing as part of the directory’s current concept. He also discusses improvements he wants to make, including better filtering and search, fuller resource details, stronger comparisons, AI-powered recommendations, more MCP resources, community submissions, curated collections and workflows. They should be understood as plans, not features the article establishes as available.

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Natural-language recommendations based on a person’s goal are likewise described as a possible future direction. The article does not provide ranked recommendations, head-to-head evaluations or user-study results.

How should you evaluate a listing?

Use AIMarketly as a discovery starting point, then check the resource itself before relying on an important claim. A practical comparison can focus on:

  • The task: Does the resource address the specific coding, marketing, automation or other problem you need to solve?
  • Category and fit: Is it a tool, skill, MCP server, prompt or another kind of resource—and does that match your workflow?
  • Integrations: Does the provider describe support for the services, APIs or development environment you depend on?
  • Listing detail: Does the directory entry give enough current information to make a useful shortlist?
  • Provider confirmation: Verify consequential details—such as capabilities, compatibility and terms—on the provider’s own page.

This is a comparison method for readers, not a process or ranking system that Adnan says AIMarketly currently uses.

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Why keeping the directory current is difficult

Adnan identifies ongoing catalog upkeep as a core challenge: products appear, change their positioning and introduce categories that did not previously exist. He characterizes the work as “Discovery → Categorization → Organization → Search → Updating” and says he is working on how resources are organized.

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His article does not specify an update schedule, listing-verification standard, ranking or deduplication method, pricing coverage, product-review process or third-party audit. Readers therefore cannot infer from the directory description alone how recently an entry was checked or how listings are selected.

Who may find it useful?

Developers looking for AI coding resources, MCP servers, APIs or related tools may use the categories to begin assembling options. Marketers may use the described content, SEO, social media, image, video and automation categories for the same discovery purpose. Adnan also invites feedback from people working with LLMs, AI agents, MCP, RAG, AI APIs, automation and developer tools.

The article’s central promise is organization and discovery across a broad set of AI-related resources. It does not establish that the catalog is comprehensive, that its entries are independently verified, or that one listing is better than another.

Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.

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AI directoriesAI toolsAIMarketlyDeveloper ToolsMCP servers

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