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Nia: 10x the context of your coding agent

Improved Cursor's performance by 27%

TL;DR

Stop hand‑feeding links and developer context to your agent. Nia is an MCP server that can index entire codebases & documentation sites, perform deep research, and more so agents like Cursor, Continue, and Cline “just know” the right answer.

In internal evals we improved Cursor’s performance by 27 % once Nia had indexed external docs models couldn’t get from their training data or searching the web.

https://youtu.be/WSqM5FmqFQM

The Problem

  • Coding agents are great with local files but fail when it comes to external context enrichment.
  • Agents are finally great at codegen, terrible at retrieving the right context.
  • You still copy‑paste GitHub and web links one‑by‑one and pray the model scrolls far enough.

Context—not generation—is now the bottleneck.

What Nia does

  • Indexes multiple repos & entire docs sites at once via an MCP server.
  • Works as MCP server and can be used inside Cursor, Cline, Continue etc.
  • Deep‑Research Agent: ask “Compare LangChain, Llama Index, Haystack,” get an auto‑generated table (pros, cons, best pick) and have all three repos pre‑indexed for later use.

Get Started in <3 minutes

  1. Grab your API key at https://app.trynia.ai/
  2. Follow instructions at https://docs.trynia.ai/integrations/nia-mcp
  3. Enjoy.

https://youtu.be/5019k3Bi8Wo?si=ERmnmo01IJ3DQfrv

My ask

  1. Try Nia today and tell us what context your agent still misses.
  2. BOOK A FREE CALL → https://calendly.com/arlanrakh/nia-ai-demo

👉 Contact me at arlan@nozomio.com

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My story

  • I’m Arlan, solo‑founder immigrant from Kazakhstan.
  • Launched my first edtech startup at 15.
  • I got kicked out of my math classes for taking investor calls, so I dropped out of high school to move to London where I raised my pre-seed in couple days.
  • I cold-emailed my way into research @ Stanford when I was 16, and worked closely with a Georgia Tech professor on a book called Cobra, a powerful interactive tool for finding defects or suspicious patterns in source code.

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