Unabyss
Confluo.in
BaseThread
Supermemory
Claude by Anthropic
mcp skills
Nia
Callio
Haystack Analytics
LinearB
GitPrime
Waydev
Swarmia
CodeClimate
Athenian
Teamplify
Set it up once and never re-explain yourself to AI again. Connect the apps you use daily - Unabyss will extract, structure, and update your context automatically. Share it with any AI tool via MCP, with granular control over what each tool can see.
Haystack is a real-time delivery analytics platform designed for engineering leaders like CTOs, VPs of Engineering, Directors of Software Engineering, and Engineering Managers. Haystack provides actionable insights that enable data-driven decision-making, aligning engineering performance with business objectives. Haystack platform integrates seamlessly with essential developer tools like GitHub and JIRA, offering a comprehensive view of team productivity and delivery efficiency.
Leading companies like AngelList, Shutterstock, Schneider Electric, and many more trust Haystack to optimize their development processes. By transforming historical Git data into objective insights, we help you identify bottlenecks and visualize trends, ensuring timely project delivery and sustained business growth. Our analytics dashboard allows you to monitor critical metrics such as cycle time, making it easier to spot inefficiencies before they escalate into costly delays.
Haystack helps engineering leaders to mitigate risks and improve workflow efficiency. With a unified view of the entire delivery lifecycle, you can track KPIs, compare performance trends, and make informed decisions that drive measurable outcomes. Our platform goes beyond merely measuring productivity; it equips you with the tools to foster continuous improvement and innovation within your teams.
Designed to scale with your organization, Haystack is the competitive advantage that data-driven engineering teams need to thrive. By leveraging analytics, you can transform your engineering operations, enhance collaboration, and accelerate your path to market success. Join top companies in harnessing the power of Haystack for a more efficient and effective engineering process.
Unabyss Haystack AnalyticsUnabyss's answer
Two core personas. First, Builders โ developers, AI consultants, and technical PMs who are MCP-native and already wiring up agents and automations; they activate through MCP naturally. Second, AI Enthusiasts โ founders, operators, marketers, and growth people who use AI every day and are tired of re-explaining their context across tools. We're expanding from this prosumer wedge toward small teams (5โ15 people), where the value shifts to a shared "company brain" and cross-project memory.
Haystack Analytics's answer:
Engineering Leaders and Managers
Unabyss's answer
Unabyss isn't just MCP connectors bolted onto keyword search. It's a full context layer that sits between your tools and your AI: it ingests data from 30+ sources, then cleans, chunks, tags, versions, and connects it into a multi-store context graph (graphs + RAG + semantic search). Your AI tools โ Claude, Cursor, any agent โ pull the right slice of context on demand over MCP, so you never re-explain yourself and never maintain manual .md files again. The structuring and retrieval layer is the moat; raw MCP connectors don't do it.
Unabyss's answer
Most memory tools (Mem0, Letta, Supermemory, Cognee, Personal.ai) or platform-native memory (ChatGPT/Claude/Gemini) lock your context inside one place or treat it as a flat store. Unabyss is MCP-first and portable: your context lives in one user-owned layer and works across every AI tool at once. You get diff-based ingestion so only what changed re-syncs, full version history with newest-version-wins conflict resolution, and iOS-style granular permissions that keep personal and company context cleanly separated โ with an audit trail and one-click revoke. It's the difference between a memory feature and a context infrastructure you control.
Unabyss's answer
Unabyss began with a simple thesis: people should own a portable context layer that any AI tool can use. We started with content creation as the wedge โ an AI ghostwriter with a deep-interview mode that captured how someone actually thinks and works โ and hit $12.5K MRR at $500+ ARPU in seven months. But users kept telling us the magic wasn't the writing; it was that "it knows me." They started asking why their other tools couldn't start from that same context. That pull pushed us to build the full context vault and go all-in on MCP: the real "wow" isn't a vault UI, it's Claude or Cursor instantly having your context with zero copy-paste. We launched on Product Hunt in May 2026 and hit #1 Product of the Day.
Unabyss's answer
Backend: Django 6 + Django REST Framework Web (product + marketing): SvelteKit โ app.unabyss.com and unabyss.com Database: PostgreSQL (including Neon) Distribution: MCP server (primary), plus REST API and OpenAI function-calling adapters Integrations: 30+ native connectors Infrastructure: Docker Compose, VPS deployment behind nginx with SSL
Unabyss's answer
Based on our record, Haystack Analytics seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Heads up: site is not loading. Ios Safari & macOS Chrome. Mixed Content: The page at 'https://usehaystack.io/' was loaded over HTTPS, but requested an insecure favicon 'http://www.usehaystack.io/favicon.ico'. This request has been blocked; the content must be served over HTTPS. - Source: Hacker News / over 5 years ago
Hey HN! I'm Julian, co-founder of Haystack (https://usehaystack.io). Weโre building one-click dashboards and alerts using Github data. While managing teams from startups to more established companies like Cloudflare, my cofounder Kan and I were constantly trying to improve our team and process. But it was pretty tough to tell if our efforts were paying off. Even tougher to tell where we could improve. We tried... - Source: Hacker News / over 5 years ago
Confluo.in - One shared memory for every AI you use. Carry context between Claude, ChatGPT and Gemini โ and stop re-explaining your project every time you switch.
LinearB - LinearB delivers software leaders the insights they need to make their engineering teams better through a real-time SaaS platform. Visibility into key metrics paired with automated improvement actions enables software leaders to deliver more.
BaseThread - One shared context every AI tool your team uses reads and writes over MCP, so Claude Code, Cursor and ChatGPT stay current together.
GitPrime - GitPrime uses data from any Git based code repository to give management the software engineering metrics needed to move faster and optimize work patterns.
Supermemory - ai second brain for all your saved stuff
Waydev - Waydev analyzes your codebase from Github, Gitlab, Azure DevOps & Bitbucket to help you bring out the best in your engineers work.