About multiagent.tools
We aggregate the best AI development tools from 21+ directories into one searchable catalog — so you can find what you need without checking a dozen sites.
Our Mission
The AI tools ecosystem is fragmented. MCP servers are on Smithery and GitHub. Skills are on SkillsMP and ClawHub. Plugins are in different marketplaces. Agents are scattered across directories. Finding the right tool means checking multiple sources, comparing data, and guessing what's actively maintained.
multiagent.tools solves this by aggregating tools from all major directories into one catalog with standardized metadata — popularity scores, freshness badges, platform support, and verified publisher indicators. We update daily via automated scrapers.
What We Track
We organize AI tools into five categories:
Our Methodology
We collect data from 21+ sources including Smithery, Glama, MCP.so, PulseMCP, MCPMarket, SkillsMP, ClawHub, GitHub Topics, and more. Our automated pipeline:
- 1 Discovers new tools from all sources daily
- 2 Deduplicates across sources using URL matching and fuzzy name comparison
- 3 Enriches with GitHub stats, descriptions, and tags
- 4 Calculates popularity score (0-100) from stars, downloads, and freshness
- 5 Updates stats daily via Vercel Cron at 06:00 UTC
Our Team
multiagent.tools is built by STACKMAKERS — a team focused on developer tooling and AI infrastructure. We believe the multi-agent future needs better discovery and standardization.
Tech Stack
multiagent.tools is built with modern, production-grade tools:
Why We Built This
In 2025-2026, the AI tools ecosystem exploded. MCP servers alone grew from a handful to 500+. But discovering them meant checking Smithery, then GitHub, then Glama, then MCP.so — each with different data, different sorting, and no way to compare across sources.
We built multiagent.tools to be the single source of truth. One catalog that aggregates everything, normalizes the data, and lets you find the best tool in seconds instead of hours. Every component has a popularity score, freshness badge, and platform compatibility — computed automatically from real data.
Our blog provides the context that raw data can't — guides on what MCP is, how to choose between tools, and tutorials for getting started. All content is SEO-optimized with keyword research from DataForSeo to ensure developers can find us when searching for AI tools.