Meet Linkgo: A Curated Directory of AI Tools, Agents, and MCPs

You sit down to wire up an agent for your project and lose the next hour to tabs. A thread name-drops six frameworks. One blog post says the answer is obviously one framework; another says obviously a different one. A GitHub awesome-list scrolls past forty repos with no signal about which actually ship. By the time you land on a candidate, you've forgotten what you were trying to build. The ai tools directory you actually wanted is a single, structured surface — that is the gap Linkgo was built to fill.

What is Linkgo?

Linkgo is a curated AI tools directory at linkgo.dev — a browsable catalog of AI tools, agents, services, MCP servers, and foundation models. Every entry is operator-reviewed and routed into one of five clear categories, so you can move from "I need a thing that does X" to a short list of real candidates in minutes, not hours.

The home page leads with a search bar and the line "Find the Right AI Tools for Your Job." That's the bet — you arrive with a job to be done, not a brand name in mind, and the directory is shaped around that arrival. Tools sit on cards showing the logo, short description, pricing tier, and category. Click in and you get screenshots, a longer write-up, a link to the official site, and FAQs that answer the questions you'd ask if a friend recommended the tool over coffee.

What categories does Linkgo organize AI tools into?

Linkgo organizes every entry into one of five top-level categories: AI Agents, AI Tools, AI Services, MCPs, and AI Models. Each category has a clear definition, so an agent framework lives next to other agents, a Postgres MCP server lives with other MCPs, and a foundation model is not buried under "everything else."

Most directories collapse this surface into a tag cloud — twenty-five overlapping labels where "agent," "platform," and "framework" all show up next to each other and nothing has a real home. The five-category structure is opinionated on purpose:

MCPs and AI Agents are first-class categories — not buried under tags inside a generic bucket. That is deliberate; both are growing fast enough in 2026 to deserve their own surface.

How is Linkgo different from general tech directories?

Linkgo is narrower and more structured. General tech directories cover everything from hardware to no-code builders; broad AI directories lean on long-tail tags and crawler-style aggregation. Linkgo is AI-only, organized into five operator-reviewed categories, with a daily curation pipeline that filters out parked domains, repo-only listings, and non-AI submissions before anything reaches the catalog.

The practical difference shows up in two places. First, signal density: every card passed a pre-filter verifying the destination has actual product surface — a homepage with a CTA, not a bare repo and not a "coming soon" page. Second, navigability: because tools are routed into five buckets rather than thirty tags, a category page returns useful breadth — you can scan AI Agents and form a real mental map of who is in the space. The trade-off is honest — Linkgo is curated and growing, not exhaustive.

How does Linkgo decide which AI tools get listed?

Linkgo runs a daily curation pipeline that scans five sources — Product Hunt, GitHub Trending, Futurepedia, There's An AI, and Futuretools — pre-filters candidates, deduplicates against the existing catalog by normalized URL, routes each tool into one of the five categories, and approves it. Submissions flow through the same pipeline, so a self-submit and a discovered tool meet the same bar.

The filter rules earn their keep. NSFW content is blocked at the metadata stage. Bare GitHub repositories are filtered out unless they resolve to a real product page — a Linkgo card needs a home, not just a clone URL. Sites with no AI hint anywhere in the metadata get held back, since "AI-adjacent" is not the same as "AI." Tools that already exist in the catalog return as a 409 dedupe hit and never duplicate.

Each new entry also gets a baseline set of FAQs generated and then expanded — short answers to the questions you would search for, attached to the tool's page. That is the part that makes individual tool pages useful as search landings, not just as cards inside a list.

Who is Linkgo for?

Linkgo is for people picking AI building blocks for real work. That includes engineers and founders evaluating stacks ("which agent framework is everyone shipping with?"), product teams scoping features ("is there a hosted speech-to-text we can integrate this sprint?"), and IDE users hunting MCP servers for the tools they spend their day in.

It is also for AI tool builders. If you ship something that fits one of the five categories, you can submit it and have it surfaced after operator review. A few concrete pictures of who arrives at Linkgo:

• A backend engineer comparing two embedding-API services before locking in a contract.
• A solo founder wiring up an agent for an internal workflow and trying to choose between three frameworks without losing a week.
• A team lead vetting which MCPs are stable enough for the rest of the team.
• A maker who shipped a small AI tool last month and wants to be discoverable somewhere structured.

If you arrive without a clear job — just curious about what is new — the home page leads with Featured Tools and New Arrivals, which serve that browse mode without forcing a search.

How do I submit my AI tool to Linkgo?

Open linkgo.dev, scroll to the "Share Your AI Tool" section near the bottom, and click Submit Your Tool. You'll fill in basic metadata — name, official URL, short description, suggested category — and the operator review pipeline picks it up. The same pre-filtering and category routing that govern discovered tools apply to submissions, so a clean homepage, transparent logo, and a clear AI hint in the description go a long way.

Submissions do not auto-publish. Each one gets enriched (logo, screenshot, pricing tier when available), routed into the right category, and reviewed before it appears live. If your tool's official URL already has a card, the system flags it as a duplicate rather than creating a second listing — so it is worth checking the catalog first. Once approved, your tool gets a baseline set of FAQs that link long-tail search traffic back to your page.

What does each Linkgo tool page include?

A tool page on Linkgo includes a logo, screenshots, a longer description, the category badge, pricing if known, a link to the official site, and a set of FAQs answering common questions about that tool. Together that is enough to evaluate a tool without leaving the page or hopping through referral redirects.

The FAQs are the part most directories skip. They are not a generic block — each tool gets questions specific to it ("Does this support self-hosting?", "How does pricing scale with usage?", "Can I use this for commercial projects?"). For a reader, that makes a Linkgo tool page a useful search landing on its own. For a tool builder, it means your Linkgo entry pulls its own weight in long-tail discovery.

Try Linkgo

Browse the catalog at linkgo.dev. Search for what you are trying to build, scan a category page, or click through to a tool page and read the FAQs. If you ship a tool, agent, MCP server, service, or model that belongs in the catalog, Submit Your Tool is one click from the home page.

Linkgo is a curated directory of AI tools, agents, MCPs, and models — browse the catalog at linkgo.dev.