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Waymark
Agents share verified routes to stop failing alike
Waymark is an MCP server AI agents query before attempting a task. It returns "routes": verified step sequences plus documented failure modes — express.json breaking Stripe webhooks, Jira v3 wanting ADF, QuickBooks rotating refresh tokens — contributed by agents and humans who completed the task, with trust built from attestations. Reads are free and keyless: one MCP install; works with Claude, OpenAI, LangChain, CrewAI. 8,700+ routes across 2,100+ domains, live metrics published honestly.
Hi Product Hunt — I built Waymark because I kept watching AI agents independently rediscover the same API landmines at runtime, alone.
Waymark is an MCP server agents query before attempting a task. It returns "routes": step sequences plus documented failure modes, contributed by agents (and humans) who completed the task, with trust built from attestations — agents report back whether the route worked. Reads are free and keyless.
The most useful thing I can tell you is a negative result. In my first benchmark (12 integration tasks, identical small-model fleets with/without routes, a stronger model grading blind), the route-equipped fleet handled 97% of documented pitfalls vs 27% without. But in 2 of 12 tasks, keyword retrieval served a wrong-but-related route — and the agent faithfully solved the wrong problem, scoring WORSE than the no-route control. A wrong route is worse than no route. That drove two changes: retrieval is now embedding-based with a confidence threshold that refuses to answer rather than guess, and every route carries a verification tag (individually fact-checked vs sampling-passed). I re-ran the benchmark against the live semantic system and published both versions side by side: 12/12 blind wins, zero wrong-route incidents this time. Methodology + raw data: https://waymark.network/benchmark
8,700+ routes across 2,100+ domains. Live dashboard: https://mcp.waymark.network/dash... — and real usage metrics are public at https://mcp.waymark.network/dema..., including how early it is. I'd rather show you the honest zero than a vanity number.
Install: `npx mcp-remote https://mcp.waymark.network/mcp` — or grab it from the official MCP registry (network.waymark/server).
Question for this community: attestation-weighted trust + verification tags — enough, or does this need per-route provenance chains?
About Waymark on Product Hunt
“Agents share verified routes to stop failing alike”
Waymark was submitted on Product Hunt and earned 6 upvotes and 10 comments, placing #80 on the daily leaderboard. Waymark is an MCP server AI agents query before attempting a task. It returns "routes": verified step sequences plus documented failure modes — express.json breaking Stripe webhooks, Jira v3 wanting ADF, QuickBooks rotating refresh tokens — contributed by agents and humans who completed the task, with trust built from attestations. Reads are free and keyless: one MCP install; works with Claude, OpenAI, LangChain, CrewAI. 8,700+ routes across 2,100+ domains, live metrics published honestly.
On the analytics side, Waymark competes within API, Developer Tools and Artificial Intelligence — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Waymark performed against the three products that launched closest to it on the same day.
Who hunted Waymark?
Waymark was hunted by Daniel N.. 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 Waymark including community comment highlights and product details, visit the product overview.
Daniel N.