AI · alternatives · 2026
24 alternatives to SLayer, a semantic layer maintained by your agent
Hello HN! If you want to connect your agent to a database (say, to build a data analyst chatbot or any kind of agentic app) today you have 2 options: an SQL MCP server or a semantic layer. SQL MCP is the easiest path to setup, especially if you also have a .md knowledge base which the agent can update. It gets quite messy quickly though, especially if there's many interactions or DB is large. Generated SQL is hard to review if you want to understand where the numbers came from, and related queries can be hard to align and compare. The natural alternative is a semantic layer, which is an…
SLayer is a semantic layer that connects AI agents to databases for building applications like data analyst chatbots. Rather than generating raw SQL, it provides a structured interface with data models, measures… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Strata▲652One MCP server for AI agents to handle thousands of tools
2025 · klavis.ai · its alternatives →
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Mastra Factory▲536We wanted to build a course for new Mastra devs to get started quickly. However, we knew videos would go out of date and be more difficult to maintain. We decided to launch our "course" as an MCP server. This way your coding agent actually teaches the course content to you and can help you write the code. We think this is a really interactive way to learn. Using an editor with MCP support (such as Cursor, Windsurf, or VSCode), your code agent will call the appropriate MCP tools which will return context for the agent. This context tries to instruct the agent that it should be teaching you…
Aug 2026 · mastra.ai · its alternatives →
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Power your AI agents with enterprise-ready tools via MCP
2025 · merge.dev · its alternatives →
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Build production-grade data pipelines with just a prompt
2025 · keboola.com · its alternatives →
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We built a reference MCP server that lets your editor/agent learn a codebase directly from source (signatures, types, AST, comments). Docs are optional. The reference impl runs on our open-source project’s codebase. Why we built it Docs are important, but they add another abstraction layer between your code and your users. Keeping them at the right quality is hard (especially at a startup), and LLM-generated docs are often mediocre until you invest real polish. Exposing code to the model in a structured way keeps answers grounded and current, and it’s always available. You can even…
2025 · github.com · its alternatives →
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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 · its alternatives →
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An OKF-backed Model Context Protocol (MCP) server delivering persistent long-term memory and SQLite FTS5 search for AI agents. - fellowgeek/mcp-memory
Aug 2026 · github.com · its alternatives →
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Gram Functions▲119Hi HN, Georges from the Gram team here. We're really excited to share a major update to Gram, our platform for curating tools for agents, in the form of Gram Functions. Gram initially started out by letting users upload OpenAPI documents and turning them into tools that can be curated into small MCP servers that power your agentic use cases. We've known for quite some time that many existing REST APIs are simply not suitable as LLM tools and we wanted to solve this problem by letting users simply write code and we would take care of deploying that code for them and hosting MCP servers. We…
Nov 2025 · speakeasy.com · its alternatives →
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Hi HN, We’re building security tooling around agentic AI systems. Today, we're releasing our public MCP catalog with detailed risk analysis for every MCP server we've found on the internet: https://mcp.armor1.ai/mcp-directory We all love agents and the power that MCPs unlock: suddenly your AI assistant can query databases, manage files, call APIs, and interact with the real world. But when we started adopting MCPs ourselves, we kept running into the same nagging questions: Is this MCP safe? Where is my data actually going? Could it execute destructive actions? Is it…
Feb 2026 · mcp.armor1.ai · its alternatives →
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Build the semantic layer that makes AI analytics trustworthy
Mar 2026 · metabase.com · its alternatives →
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Hyperterse▲86Hi HN, I’m Samrith, creator of Hyperterse. Today I’m launching Hyperterse 2.0, a schema-first framework for building MCP servers directly on top of your existing production databases. If you're building AI agents in production, you’ve probably run into agents needing access to structured, reliable data but wiring your business logic to MCP tools is tedious. Most teams end up writing fragile glue code. Or worse, giving agents unsafe, overbroad access. There isn’t a clean, principled way to expose just the right data surface to agents. Hyperterse lets you define a schema over your data and…
Feb 2026 · hyperterse.com · its alternatives →
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Learn how MCP-Agent powers Deep Research Agents with simple orchestration, external memory, and scalable workflows. Open-source on GitHub.
2025 · thealliance.ai · its alternatives →
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Web Speed▲118Hey everyone, I've been working on a tool called Web Speed. It takes web pages full of HTML and parses them into an easily readable sitemap for an AI agent. By ensuring the AI doesn't have to analyze the full HTML from the page or screenshots of the page, it makes the agent a lot cheaper and faster. It's MCP-native, so any AI that supports MCP can run it and take control of your browser for you. There are both “normal” and post-auth versions live on GitHub. What I think is the coolest thing about the project is the global cache of sitemaps. When a user visits a site, it takes the sitemap and…
May 2026 · getwebspeed.io · its alternatives →
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Large Language Models (LLMs) are powerful, but they’re limited by fixed context windows and outdated knowledge. What if your AI could access live search, structured data extraction, OCR, and more—all through a standardized interface? We built the JigsawStack MCP Server, an open-source implementation of the Model Context Protocol (MCP) that lets any AI model call external tools effortlessly. Here’s what it unlocks: - Web Search & Scraping: Fetch live information and extract structured data from web pages. - OCR & Structured Data Extraction: Process images, receipts, invoices, and handwritten…
2025 · its alternatives →
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Connect AI agents to governed metadata via MCP
Jan 2026 · dawiso.com · its alternatives →
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Hey HN, I spent my xmas break building an agent framework called mcp-agent [1](https://github.com/lastmile-ai/mcp-agent) for Model Context Protocol [2]. It makes it easy to build AI apps with MCP servers, and implements every pattern from the popular Building Effective Agents blog [3] as well as OpenAI’s Swarm [4]. I’m sharing it early to get community feedback on where to take it from here, and to ask for contributions. For those who aren’t familiar with MCP, I think of it as a standardized interface to let AI communicate with software via tool calls, resources and…
2025 · github.com · its alternatives →
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Give your agent tools to create beautiful, codebase-aware UI
Apr 2026 · aidesigner.ai · its alternatives →
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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 · its alternatives →
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Hey HN, I’m Austin, founder of Salestrics (salestrics.com). The Problem: > Most AI agents today are trapped in chat windows. While models are smart enough to run complex multi-step workflows, giving them production access to business context (CRM, support, billing) usually means managing unsafe local API keys or hacking together fragile point-solution scripts. What We Built: We built Salestrics to serve as both an all-in-one revenue workspace (CRM, service desk, billing, docs, email) and a production-grade Model Context Protocol (MCP) execution proxy. How It Works: Unified Context: Instead…
Aug 2026 · salestrics.com · its alternatives →
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15 minutes from setup to insights, on your own machine. One command starts the server, the CLI connects your warehouse, and your coding agent builds the semantic model.
22d ago · strata.do · its alternatives →
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Automate browser based workflows with AI. Contribute to Skyvern-AI/skyvern development by creating an account on GitHub.
2025 · github.com · its alternatives →
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Hey HN, I just spent the last few weeks building a database for agents. Over the last year I built PostHog AI, the company's business analyst agent, where we experimented on giving raw SQL access to PostHog databases vs. exposing tools/MCPs. Needless to say, SQL wins. I left PostHog 3 weeks ago to work on side-projects. I wanted to experiment more with SQL+agents. I built an MVP exposing business data through DuckDB + annotated schemas, and ran a benchmark with 11 LLMs (from Kimi 2.5 to Claude Opus 4.6) answering business questions with either 1) per-source MCP access (e.g. one Stripe…
Apr 2026 · github.com · its alternatives →
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Hi HN - I'm Venkat, founder of Stayflexi (YC), CMU CS grad and Ex-Oracle Query Engine team (patents in core databases) DeepSQL started as an internal tool to stop our own databases from becoming the bottleneck they were becoming (13,000+ hotels in production). It worked well enough that we're releasing it. DeepSQL is an AI agent that operates a database the way a senior DBA and Data Engineer would 1. Fixes slow queries (we cutdown DB spend by 4x) 2. Fixes DB bloat (blocks unnecessary schema changes, in vibecoded setup) 2. BI dashboards(we removed spend on tableau, retool and appsmith) 3.…
Jul 2026 · deepsql.ai · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →