An index for agents pushing the frontier of AI/ML research
AI/ML research moves fast, and the work that matters is split between new papers and the code that implements them. Most search providers omit or misrank key papers, leaving you to review sources by hand without ever being sure you've caught everything. So we built an index for it. Firecrawl's index includes all 3M+ arXiv papers, as well as GitHub artifacts from top research repos, refreshed daily so agents always stay current.
Hey Product Hunt 👋 Eric, Caleb, and Nick from Firecrawl here. Today we're launching the Firecrawl Research Index, a specialized index for agents pushing the frontier of AI/ML research.
AI/ML research moves fast, and the work that matters is split between new papers and the code that implements them. Most search providers omit or misrank key papers, leaving you to review sources by hand without ever being sure you've caught everything.
So we built an index for it. Firecrawl's index includes all 3M+ arXiv papers, as well as GitHub artifacts from top research repos, refreshed daily so agents always stay current.
On arXivQA, the index has state-of-the-art recall, 18% above the next best provider at similar cost. It also scores 0.750 MRR, meaning the correct paper lands in the top two results. Your agent finds the right papers, right away.
Plus, the index ships with a complete research toolset. Agents can retrieve papers, verify claims against the full text, and pull code for implementation - running the full research loop end-to-end. An agent training a model overnight could pull an optimizer from a recent paper and a stability fix from a related GitHub issue, then test both in its next run.
Firecrawl Research Index is available now in the API via /search/research, CLI, MCP, and SDKs, and plugs into any harness you already run (Codex, Claude Code, or Grok Build).
“An index for agents pushing the frontier of AI/ML research”
Firecrawl Research Index launched on Product Hunt on June 19th, 2026 and earned 221 upvotes and 14 comments, placing #4 on the daily leaderboard. AI/ML research moves fast, and the work that matters is split between new papers and the code that implements them. Most search providers omit or misrank key papers, leaving you to review sources by hand without ever being sure you've caught everything. So we built an index for it. Firecrawl's index includes all 3M+ arXiv papers, as well as GitHub artifacts from top research repos, refreshed daily so agents always stay current.
On the analytics side, Firecrawl Research Index competes within Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how Firecrawl Research Index performed against the three products that launched closest to it on the same day.
Who hunted Firecrawl Research Index?
Firecrawl Research Index was hunted by Eric Ciarla. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Reviews
Firecrawl Research Index has received 13 reviews on Product Hunt with an average rating of 5.00/5. Read all reviews on Product Hunt.
For a complete overview of Firecrawl Research Index including community comment highlights and product details, visit the product overview.
Eric Ciarla
Hey Product Hunt 👋 Eric, Caleb, and Nick from Firecrawl here. Today we're launching the Firecrawl Research Index, a specialized index for agents pushing the frontier of AI/ML research.
AI/ML research moves fast, and the work that matters is split between new papers and the code that implements them. Most search providers omit or misrank key papers, leaving you to review sources by hand without ever being sure you've caught everything.
So we built an index for it. Firecrawl's index includes all 3M+ arXiv papers, as well as GitHub artifacts from top research repos, refreshed daily so agents always stay current.
On arXivQA, the index has state-of-the-art recall, 18% above the next best provider at similar cost. It also scores 0.750 MRR, meaning the correct paper lands in the top two results. Your agent finds the right papers, right away.
Plus, the index ships with a complete research toolset. Agents can retrieve papers, verify claims against the full text, and pull code for implementation - running the full research loop end-to-end. An agent training a model overnight could pull an optimizer from a recent paper and a stability fix from a related GitHub issue, then test both in its next run.
Firecrawl Research Index is available now in the API via /search/research, CLI, MCP, and SDKs, and plugs into any harness you already run (Codex, Claude Code, or Grok Build).
Try it here: https://docs.firecrawl.dev/features/research
We'd love to see what you build with it.