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Forecall
Lint your MCP tool descriptions before AI agents call them
AI agents choose and call MCP tools by reading their names, descriptions and input schemas. Vague text means the wrong tool, wrong arguments, or no call at all. Forecall scores each tool out of 100 on six items (purpose, when to use, arguments, return value, constraints, examples), finds tools that are easy to mix up, and explains every issue with a code and severity. Free on the web with no sign-up, or run npx forecall lint locally and in CI.
Hi Product Hunt! AI agents pick a tool by reading its name, description and input schema, and nothing else. When we scored 8 well-known MCP servers (126 tools), their averages ranged from 33 to 70 out of 100, and Notion's official server alone had 57 pairs of tools an AI can easily mix up.
Forecall is a static linter for that text. It scores each tool on six items, explains every issue with a code and a severity, and points out tools that are easy to confuse. It's free on forecall.dev with no sign-up, and the same rules run locally with npx forecall lint (nothing is uploaded), so you can fail a CI job when the average drops.
Next, we're building Evaluations that measure how often real models choose and call your tools correctly. I'd love your feedback on the scoring rules: what should a good tool description say?
About Forecall on Product Hunt
“Lint your MCP tool descriptions before AI agents call them”
Forecall was submitted on Product Hunt and earned 6 upvotes and 3 comments, placing #38 on the daily leaderboard. AI agents choose and call MCP tools by reading their names, descriptions and input schemas. Vague text means the wrong tool, wrong arguments, or no call at all. Forecall scores each tool out of 100 on six items (purpose, when to use, arguments, return value, constraints, examples), finds tools that are easy to mix up, and explains every issue with a code and severity. Free on the web with no sign-up, or run npx forecall lint locally and in CI.
On the analytics side, Forecall competes within API, Developer Tools and Artificial Intelligence — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Forecall performed against the three products that launched closest to it on the same day.
Who hunted Forecall?
Forecall was hunted by Hiroki Nomura. 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.
For a complete overview of Forecall including community comment highlights and product details, visit the product overview.
Hiroki Nomura