A factual side-by-side of AI Agents Listing and Glama: coverage, pricing, curation and ranking.
| Glama | AI Agents Listing | |
|---|---|---|
| Listings | 80K+ auto-indexed MCP servers, 633K indexed tools | A curated, growing catalog across all three verticals |
| Scope | MCP servers, clients, hosting, gateway and a directory API | AI agents, MCP servers and agent skills, cross-linked |
| Pricing | Category sponsor $200/mo, featured $600/mo, both labeled as ads | Free listings forever; transparent one-time upgrade tiers |
| Coverage | AI agentsMCP serversAgent skills | AI agentsMCP serversAgent skills |
| Notable | A to F quality grades and security audits on every server | Every listing reviewed by a human; rankings from engagement, never from spend |
Glama is the heavyweight of MCP discovery, and we will not pretend otherwise. It auto-indexes more than 80,000 servers, makes 633,000 individual tools searchable, and layers on data nobody else has: A to F quality and maintenance grades, security audits, hosting and language facets, GitHub stats, an in-browser MCP Inspector, and a directory API. It also handles advertising the right way, with paid placements clearly labeled and a stated firewall between payment and rankings. That trust model deserves credit, and it is the one we follow too.
Glama's depth comes with two boundaries. First, it is MCP-only. There is no agents vertical and no skills vertical, so it maps one layer of the stack in extraordinary detail while the other two stay out of frame. Second, auto-indexing at that scale sweeps in a long tail of low-quality wrapper servers; the grades help you filter, but the flood is real, and the directory ultimately feeds Glama's gateway and hosting business.
We index AI agents, MCP servers, and agent skills in one place and cross-link them, which no MCP-only registry can do. Instead of auto-indexing everything, a human reviews each submission before it publishes, so the catalog grows slower but stays clean. Listing is free forever, upgrades are one-time purchases at published prices, and the Heat leaderboard ranks on engagement that no payment can influence.
To be plain about scale: our MCP catalog is a small fraction of Glama's 80K, and we do not yet match its per-server data depth. What we offer instead is the stack view: the agents that use a server and the skills that extend them, connected.
Use Glama if you live inside the MCP layer and want the deepest technical data on servers, grades, audits, and tooling included. Use aiagentslisting if you are assembling a full agentic stack and want agents, servers, and skills reviewed, categorized, and linked to each other.