Alternatives
Products that do what Waymark does
Agents share verified routes to stop failing alike
- 1AK
I shipped a wiki layer for AI agents that uses markdown + git as the source of truth, with a bleve (BM25) + SQLite index on top. No vector or graph db yet. It runs locally in ~/.wuphf/wiki/ and you can git clone it out if you want to take your knowledge with you. The shape is the one Karpathy has been circling for a while: an LLM-native knowledge substrate that agents both read from and write into, so context compounds across sessions rather than getting re-pasted every morning. Most implementations of that idea land on Postgres, pgvector, Neo4j, Kafka, and a dashboard. I…
Apr 2026 · github.com
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Papermark Agents▲143Let AI agents run your next deal, fundraise or data room
Jun 2026 · papermark.com
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Scan your website to see how ready it is for AI agents.
Apr 2026 · isitagentready.com
- 6TT
Hi HN, I'm the CEO at https://replay.io. We've been building a time travel debugger for web apps for several years now (previous HN post: https://news.ycombinator.com/item?id=28539247) and are combining our tech with AI to automate the debugging process. AIs are really good at writing code but really bad at debugging -- it's amazing to use Claude to prompt an app into existence, and pretty frustrating when that app doesn't work right and Claude is all thumbs fixing the problem. The basic reason for this is a lack of context. People can use devtools to understand…
2025 · nut.new
- 7WE
Hey HN! We’ve been building an MCP server to help AI-assisted web app developers by using browser agents to test whether changes made by an AI inside an editor actually work. We've been testing it on scenarios like verifying new flows in a UI, or checking that sending a chat request triggers a response. The idea is to let your coding agent both code and evaluate if what it did was correct. Here’s a short demo with Cursor: https://www.youtube.com/watch?v=_AoQK-bwR0w When building apps, we found the hardest part of AI-assisted coding isn’t the coding—it’s tedious point-and-click…
2025 · github.com
- 8RA
Hey HN! A few months ago we shared mcp-agent (https://github.com/lastmile-ai/mcp-agent) [1][2], a lightweight framework that implements every agent pattern from Anthropic’s Building Effective Agents blog [3] and handles MCP server/client management seamlessly. Our core bet is that connecting LLMs to tools, resources, and external systems will soon be MCP-native by default. Today we're launching a significant update: Agents as MCP servers. Currently "agentic" behavior exists only on the MCP client side – clients like Claude or Cursor use MCP servers to solve tasks.…
2025 · github.com
- 9CS
We now write most of our code with agents. For a while, PRs piled up, causing review fatigue, and we had this sinking feeling that standards were slipping. Consistency is tough at this volume. I’m sharing the solution we found, which has become our main product. Continue (https://docs.continue.dev) runs AI checks on every PR. Each check is a source-controlled markdown file in `.continue/checks/` that shows up as a GitHub status check. They run as full agents, not just reading the diff, but able to read/write files, run bash commands, and use a browser. If it finds…
Feb 2026 · docs.continue.dev
- 10SM
I built this because I got tired of watching Claude Code read through massive files just to find a few functions. Sourcerer lets AI agents search code semantically and grab exactly the code chunks they need instead of burning tokens on whole files. It uses tree-sitter to parse your codebase and creates a searchable index. So instead of "read auth.py (538 lines)", an agent can search for "user authentication logic" and get back just the relevant functions. Demo: https://asciinema.org/a/736638 GitHub: https://github.com/st3v3nmw/sourcerer-mcp
2025 · github.com
- 11OA
As AI agents autonomously write and deploy code, there's no standard for verifying that what they shipped actually satisfies business requirements. OQP is an attempt to define that standard. It's MCP-compatible and defines four core endpoints: - GET /capabilities — what can this agent verify? - GET /context/workflows — what are the business rules for this workflow? - POST /verification/execute — run a verification workflow - POST /verification/assess-risk — what is the risk of this change? The analogy we keep coming back to: what OpenAPI did for REST APIs,…
Apr 2026 · github.com
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More than a decade ago, I adopted the self-imposed rule, if I answer a question more than once, the third time I need to be able to answer with a URL. Today, I published one very large URL - a book distilling what I learned from helping people work remotely at GitHub, and I wanted to rethink my rule for the age of AI. What if, instead of a URL, I could create an interactive experience that could tailor the guidance to your particular situation? What I ended up building was an Open and Async Advisor MCP server. To install (in claude or any other AI): > claude mcp add open-async -- npx -y…
Jul 2026 · github.com
- 16MT
At our company we needed some sort of unified logging for our AI agents (devs using cursor, internal agents for checking documents, handling client requests etc) and we came up with a tool that we've decided to make available as a SaaS. With it your agents will report their progress automatically, and you'll get a unified log across projects that you can monitor on your dashboard, query through our api, set up slack and zapier hooks or even push notifications to your mobile. You can try it out for free, any feedback would be most appreciated, thanks.
2025 · taskerio.com
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ask an agent to buy something, and it hits a wall. Why?
Mar 2026
- 18MM
Hey HN! I’m Gui from deco (decocms.com). We’ve been using this tool internally as the foundation for a few customer AI platforms, and today we’re open-sourcing it as MCP Mesh. MCP is quickly becoming the standard for agentic systems, but… once you go past a couple servers it turns into the same problems for every team: - M×N config sprawl (every client wired to every server, each with its own JSON + ports + retries) - Token + tool bloat (dumping tool definitions into every prompt doesn’t scale) - Credentials + blast radius (tokens scattered across clients, hard to audit, hard to revoke) - No…
Dec 2025 · github.com
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Dec 2025 · agentdiff.dev
- 20WM
I’m the developer behind the Web MCP at Bright Data. We just launched a free tier so any AI Engineer/ Vibe coder can give their LLM real web access — 5,000 requests/month at no cost. Unlike most MCP servers that wrap a single SaaS API (e.g. Gmail, GitHub), the Web MCP wraps the entire internet. It handles JS-heavy sites, auto-solves CAPTCHAs, and returns clean Markdown your model can use. Free tier includes: search_engine → search results from Google/Bing/Yandex scrape_as_markdown → fetch any URL as clean, LLM-friendly Markdown (with CAPTCHA handling) Quick start:…
2025 · github.com
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Empower AI coding agents to build APIs and MCP servers
Jun 2026 · agentback.dev
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