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Muvon
octomind
Rust2025–2026
Muvon / octomind

octomind

Open-source AI coding agent and agent runtime: one binary, any model, MCP-native. Runs in terminal, CI, or as a daemon.

2Distinct people
4Mentions
0Explicit recommenders
657GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Open-source AI coding agent and agent runtime: one binary, any model, MCP-native. Runs in terminal, CI, or as a daemon.

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month4 dated mentions

Observed mentions: 2025-06-10 09:48:32 UTC to 2026-10-31 04:54:13 UTC.

01232025-06-01 00:00:00 UTC to 2025-07-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 commentsJun 20252025-07-01 00:00:00 UTC to 2025-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-08-01 00:00:00 UTC to 2025-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-09-01 00:00:00 UTC to 2025-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-10-01 00:00:00 UTC to 2025-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-11-01 00:00:00 UTC to 2025-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-12-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-01-01 00:00:00 UTC to 2026-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-02-01 00:00:00 UTC to 2026-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsFeb 20262026-03-01 00:00:00 UTC to 2026-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-01 00:00:00 UTC to 2026-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-05-01 00:00:00 UTC to 2026-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-06-01 00:00:00 UTC to 2026-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-07-01 00:00:00 UTC to 2026-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-08-01 00:00:00 UTC to 2026-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-09-01 00:00:00 UTC to 2026-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-10-01 00:00:00 UTC to 2026-11-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsOct 2026

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jun 20252025-06-01 00:00:00 UTC2025-07-01 00:00:00 UTC312
Jul 20252025-07-01 00:00:00 UTC2025-08-01 00:00:00 UTC000
Aug 20252025-08-01 00:00:00 UTC2025-09-01 00:00:00 UTC000
Sep 20252025-09-01 00:00:00 UTC2025-10-01 00:00:00 UTC000
Oct 20252025-10-01 00:00:00 UTC2025-11-01 00:00:00 UTC000
Nov 20252025-11-01 00:00:00 UTC2025-12-01 00:00:00 UTC000
Dec 20252025-12-01 00:00:00 UTC2026-01-01 00:00:00 UTC000
Jan 20262026-01-01 00:00:00 UTC2026-02-01 00:00:00 UTC000
Feb 20262026-02-01 00:00:00 UTC2026-03-01 00:00:00 UTC000
Mar 20262026-03-01 00:00:00 UTC2026-04-01 00:00:00 UTC000
Apr 20262026-04-01 00:00:00 UTC2026-05-01 00:00:00 UTC000
May 20262026-05-01 00:00:00 UTC2026-06-01 00:00:00 UTC000
Jun 20262026-06-01 00:00:00 UTC2026-07-01 00:00:00 UTC000
Jul 20262026-07-01 00:00:00 UTC2026-08-01 00:00:00 UTC000
Aug 20262026-08-01 00:00:00 UTC2026-09-01 00:00:00 UTC000
Sep 20262026-09-01 00:00:00 UTC2026-10-01 00:00:00 UTC000
Oct 20262026-10-01 00:00:00 UTC2026-11-01 00:00:00 UTC110

What Hacker News says

4 sources
Hi HN, I've been working on Octomind, an AI development assistant that addresses two problems I kept running into: 1. *Cost blindness* - Most AI tools don't show you what you're spending until the bill arrives 2. *Model inefficiency* - Using GPT-4 for everything when simpler tasks could use cheaper models *What makes it different:* *Real-time cost display:* Every interaction shows exactly what you're spending: ``` [~$0.05] > "Explain this algorithm" [~$0.12] > "Refactor for better performance" [~$0.18] > "Generate comprehensive tests" ``` *Intelligent model routing:* Configure different models for different task types. Simple queries go to cheap models (Claude Haiku, GPT-3.5), complex reasoning goes to premium models (Claude 3.5 Sonnet, GPT-4). *MCP server integration:* This is the part I'm most excited about. You can add specialized AI
Read the rest
agents through configuration alone: ```toml [mcp.servers.code_reviewer] model = "openrouter:anthropic/claude-3-haiku" ``` Now `agent_code_reviewer(task="review this function")` is available in your session. No custom code needed. *Multimodal CLI:* ``` > /image screenshot.png > "Debug this UI layout issue" ``` *Technical details:* - Written in Rust for performance - Supports 6+ AI providers (OpenRouter, OpenAI, Anthropic, Google, Amazon, Cloudflare) - Session-based architecture with full conversation history - Built-in development tools via MCP (file operations, shell commands, etc.) *Real usage example:* Last week I used it to refactor a complex authentication system. Total cost: $0.23 for what would have been 3+ hours of manual work. The cost visibility helped me optimize my prompts and model selection. *Installation:* ```bash curl -fsSL https://raw.githubusercontent.com/muvon/octomind/main/instal... | bash ``` The project is open source (Apache 2.0): https://github.com/muvon/octomind I'd love feedback from the HN community. What features would make AI development tools more useful for your workflows? Are you tracking AI costs in your projects? *Demo:* https://asciinema.org/a/wpZmOSOgFXp8HRzTltncgN7e3
In [dead]
Hey everyone! After bouncing between ChatGPT, Claude, and countless VS Code extensions for months, I got frustrated with the constant context switching and re-explaining my codebase to AI. So we built *Octomind* - an open-source AI assistant that actually understands your project and remembers what you've worked on. ## What's different? *No more copy-pasting code snippets.* Octomind has semantic search built-in, so when you ask "how does auth work here?" it finds the relevant files automatically. When you say "add error handling to the login function," it knows exactly where that is. *Built-in memory system.* It remembers your architectural decisions, bug fixes, and coding patterns. No more explaining the same context over and over. *Real cost tracking.* Shows exactly what each conversation costs across OpenAI, Claude, OpenRouter, etc. I
Read the rest
was shocked to see I was spending $40/month on random API calls before this. *Multimodal support.* Drop in screenshots of error messages or UI mockups - works across all providers. ## The workflow that sold me: ``` > "Why is this React component re-rendering so much?" [Finds component, analyzes dependencies, explains the issue] > "Fix it" [Implements useMemo, shows the diff, explains the change] > /report [Shows: $0.03 spent, 2 API calls, 15 seconds total] ``` One conversation, problem solved, cost tracked. ## Looking for feedback on: - *Does this solve a real pain point for you?* Or are you happy with your current AI workflow? - *What's missing?* We're thinking about adding team collaboration features - *Performance concerns?* It's built in Rust, but curious about your experience The whole thing is Apache 2.0 licensed on GitHub. Would love to hear what you think - especially if you try it and it doesn't work as expected. *Try it:* `curl -fsSL https://raw.githubusercontent.com/muvon/octomind/main/instal... | bash` *Repo:* https://github.com/muvon/octomind Really curious to hear your thoughts. What would make this actually useful for your daily coding?
In Octomind – AI dev assistant that remembers your codebase

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