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We interfaced single-threaded C++ with multi-threaded Rust

https://antithesis.com/blog/2026/rust_cpp/
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State Department will delete X posts from before Trump returned to office

https://text.npr.org/nx-s1-5704785
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AI Skills Marketplace

https://skly.ai
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Show HN: A fast TUI for managing Azure Key Vault secrets written in Rust

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Discuss – Do AI agents deserve all the hype they are getting?

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ChatGPT is changing how we ask stupid questions

https://www.washingtonpost.com/technology/2026/02/06/stupid-questions-ai/
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Zig Package Manager Enhancements

https://ziglang.org/devlog/2026/#2026-02-06
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Neutron Scans Reveal Hidden Water in Martian Meteorite

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France's homegrown open source online office suite

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SpaceX Delays Mars Plans to Focus on Moon

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Jeremy Wade's Mighty Rivers

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Show HN: MCP App to play backgammon with your LLM

https://github.com/sam-mfb/backgammon-mcp
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AI Command and Staff–Operational Evidence and Insights from Wargaming

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1•tomwphillips•15m ago•0 comments

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https://steve-yegge.medium.com/the-anthropic-hive-mind-d01f768f3d7b
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https://addisoncrump.info/research/a-horrible-conclusion/
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2•mitchbob•38m ago•1 comments
Open in hackernews

Show HN: I built an MCP server to connect AI agents to your DWH

1•karakanb•2mo ago
Hi all, this is Burak, I am one of the makers of Bruin CLI (https://github.com/bruin-data/bruin). We built an MCP server that allows you to connect your AI agents to your DWH/query engine and make them interact with your data.

A bit of a back story: we started Bruin as an open-source CLI tool that brings together data ingestion, transformation, quality and governance. You can build data pipelines using SQL and Python, ingest data from many sources, run data quality checks and some more stuff, open-source. The goal has been to build a CLI experience that would make humans productive.

After some time, agents popped up, and when we started using them heavily for our own development stuff, it became quite apparent that we might be able to offer similar capabilities for data engineering tasks. Agents can already use CLI tools, and they have the ability to run shell commands, which meant that they could technically use Bruin CLI as well.

Our initial attempts were around building a simple `AGENTS.md` file with a set of instructions on how to use Bruin. It worked fine to a certain extent; however, it came with its own set of problems, primarily around maintenance. Every new feature/flag meant more docs to sync. It also meant the file needed to be distributed somehow to all the users, which would be a manual process.

We then started looking into MCP servers: while they are great to expose remote capabilities, for a CLI tool, it meant that we would have to expose pretty much every command and subcommand we had as new tools. This meant a lot of maintenance work, a lot of duplication, and a large number of tools which bloat the context.

Eventually, we landed on a middle-ground: expose only documentation navigation, not the commands themselves. In that spirit, we ended up with just 3 tools: - `bruin_get_overview` - `bruin_get_docs_tree` - `bruin_get_doc_content`

The agent uses MCP to fetch docs, understand capabilities, and figure out the correct CLI invocation. Then it just runs the actual Bruin CLI in the shell. This means less manual work for us, and making the new features in the CLI automatically available to everyone else.

You can now use Bruin CLI to connect your AI agents, such as Cursor, Claude Code, Codex, or any other agent that supports MCP servers, into your DWH. Given that all of your DWH metadata is in Bruin, your agent will automatically know about all the business metadata necessary.

Here's a quick video of me demoing the tool: https://www.youtube.com/watch?v=604wuKeTP6U

All of this is fully open-source, and you can run it anywhere.

Bruin MCP works out of the box with: - BigQuery - Snowflake - Databricks - Athena - Clickhouse - Synapse - Redshift - Postgres - DuckDB - MySQL

I would love to hear your thoughts and feedback on it, thanks!

https://github.com/bruin-data/bruin

Comments

cookiejest•2mo ago
you can improve the quality of your agents using a centralised mcp server that only has the specific tools and datasets the agent needs for a specific task. One of the ones that works for us is https://contextgate.ai. We can manage connections as a team and make many toolboxes from them