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Updated: 4 min 3 sec ago

Burp Suite Extension with MCP Server

Fri, 04/11/2025 - 8:39pm

Article URL: https://github.com/swgee/BurpMCP

Comments URL: https://news.ycombinator.com/item?id=43660248

Points: 2

# Comments: 0

Categories: Hacker News

Neelcamp – Making Parenting Easier

Fri, 04/11/2025 - 8:37pm

Article URL: https://neelcamp.com

Comments URL: https://news.ycombinator.com/item?id=43660232

Points: 1

# Comments: 1

Categories: Hacker News

Awe – Modern compiler for Algol W

Fri, 04/11/2025 - 8:28pm

Article URL: https://github.com/glynawe/awe

Comments URL: https://news.ycombinator.com/item?id=43660178

Points: 2

# Comments: 0

Categories: Hacker News

WoT.php

Fri, 04/11/2025 - 8:19pm
Categories: Hacker News

Where We Are Headed

Fri, 04/11/2025 - 8:08pm
Categories: Hacker News

I'm building a tool to unblock creativity when you feel stuck

Fri, 04/11/2025 - 7:58pm

Article URL: https://creact.ai/

Comments URL: https://news.ycombinator.com/item?id=43660027

Points: 1

# Comments: 1

Categories: Hacker News

Show HN: HelixDB – Native Graph and Vector Types for RAG and Retrieval

Fri, 04/11/2025 - 7:54pm

Hey HN! I’m building HelixDB with a college friend – a database that natively supports both graph and vector types.

It’s designed for AI-driven apps like RAG, vector search, code indexing, and agent frameworks where you need both explicit relationships and similarity.

Over the past week we've expanded our query language, released vector types, and two SDKs (Python & TypeScript), making it easy to insert and query data. HelixDB is open source, super easy to self-host, and we offer a managed service.

If you're building anything involving retrieval, we’d love your feedback!

How We Built HelixDB:

We came up with the idea for Helix while building a graph database as a side-project in Rust. Reading some research papers on RAG setups, I realised there was a lot of infrastructure setup to get started. You need your own server, a graph database, a vector database and then some bespoke middleman software to link them together.

After looking into how vectors work I discovered you can (kind of) abstract it into a graph. The vectors are just nodes with coordinates! And edges represent neighbour links. I realised I could link this up to the current graph infrastructure, allowing traversals in conjunction with similarity searches.

The way Helix works, from a low level, is you have four main types in respective tables. You have graph nodes, graph edges, vector nodes, and vector edges. The vector edges are irrelevant to developers (they just store the neighbour link for the similarity algorithm). The vector nodes work in the same way you'd use vectors in Pinecone or Qdrant by utilising HNSW. Likewise, the graph nodes work the same as they would in Neo4J or Neptune. The graph edges, however, are where things get interesting; you are able to define relationships between graph nodes, but also vectors, meaning you can have explicit dependencies between vectors and nodes or vice versa.

So, you can run a similarity search, then walk the graph to get more structured context. Or the other way around.

How Helix Works:

When you run Helix, it spins up as its own server (like a Docker container). To query it, you hit an auto-generated API endpoint.

Out of ignorance, I used to think databases compiled their queries and ran them like functions — like in normal programming. Turns out they don’t, and I never understood why that wasn’t the norm. So, like with what SpaceTimeDB is doing, we made Helix queries deployable. You write a query, and it gets built directly into the database as its own endpoint. This avoids the overhead of sending entire query strings over the network and cuts latency down a lot (and also prevents injections).

I've put an awful lot of work into this so if you could please star the Github and share it around I'd be very grateful

Comments URL: https://news.ycombinator.com/item?id=43659999

Points: 1

# Comments: 0

Categories: Hacker News

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