Battam1111/Myco
by Various
Self-evolving cognitive organism for AI agents — eternal devouring, eternal evolution.
MCP
Battam1111/Myco
Added 1 June 2026
Overview
Myco is a Rust-based framework for building self-modifying AI agents that evolve their own code and behavior over time. It implements a cognitive organism pattern where agents continuously rewrite their own logic based on experience and environmental feedback.
Best for
Best for
Researchers and hobbyists exploring self-modifying AI agent architectures
Use cases
- Building autonomous agents that adapt their decision-making logic without human intervention
- Creating long-running AI systems that improve their own algorithms through iterative self-modification
- Experimenting with emergent behavior in agent-based simulations or game AI
How to use
Install
cargo build --release --workspace Tools exposed
RustNode.jsPython
Tested with
Claude Code, Claude Desktop, Cursor, Windsurf, Zed, OpenClaw
Notes
Myco is a Rust-based framework for building self-modifying AI agents that evolve their own code and behavior over time. It implements a cognitive organism pattern where agents continuously rewrite their own logic based on experience and environmental feedback.
63 stars on GitHub. Last updated 2026-05-31. Licensed MIT.
Use cases
- Building autonomous agents that adapt their decision-making logic without human intervention
- Creating long-running AI systems that improve their own algorithms through iterative self-modification
- Experimenting with emergent behavior in agent-based simulations or game AI
Pros
- Novel self-evolution approach enables agents to discover optimizations beyond initial design
- Rust implementation provides memory safety and performance for long-running agent loops
- Open-source with permissive license allows full customization and study
Cons
- Small community (63 stars) means limited documentation, examples, and support
- Self-modifying code introduces unpredictable behavior and debugging challenges
- Experimental nature makes it unsuitable for production-critical applications
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Novel self-evolution approach enables agents to discover optimizations beyond initial design
- Rust implementation provides memory safety and performance for long-running agent loops
- Open-source with permissive license allows full customization and study
Cons
- Small community (63 stars) means limited documentation, examples, and support
- Self-modifying code introduces unpredictable behavior and debugging challenges
- Experimental nature makes it unsuitable for production-critical applications
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
Get the free Developer’s Field Guide
A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.
Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.