# Evolver — GEP-Powered Self-Evolving Engine for AI Agents

> An open-source self-evolving engine that uses Gene Expression Programming to let AI agents audit, adapt, and improve their own skill libraries over time.

## Install

Save as a script file and run:

# Evolver — GEP-Powered Self-Evolving Engine for AI Agents

## Quick Use
```bash
npm install -g @evomap/evolver
evolver init --workspace ./my-agent
evolver evolve --cycles 10 --task "optimize API error handling"
```

## Introduction
Evolver is an open-source engine that brings self-evolution to AI agents through Gene Expression Programming (GEP). It maintains auditable Genes, Capsules, and Events that let agents improve their skill libraries autonomously while keeping a full audit trail of every change.

## What Evolver Does
- Implements GEP-based evolution for agent skill optimization
- Maintains a versioned library of Genes (atomic skills) and Capsules (skill bundles)
- Records Events that trace every evolution step for auditability
- Supports MCP and A2A protocols for agent interoperability
- Provides a CLI and Node.js API for integration into existing agent systems

## Architecture Overview
Evolver models agent capabilities as a population of Genes — small executable skill units that can be composed into Capsules. The evolution loop evaluates Gene fitness against task outcomes, selects high-performing variants, applies crossover and mutation operators, and commits improved Genes back to the library. An event log records every mutation, selection, and fitness evaluation for full traceability.

## Self-Hosting & Configuration
- Install via npm as a global CLI tool or project dependency
- Initialize a workspace with seed Genes for your domain
- Configure evolution parameters: population size, mutation rate, fitness function
- Set up persistent storage for the Gene library and event history
- Integrate with existing agents via MCP server mode

## Key Features
- Auditable evolution with full event history and Gene versioning
- GEP-based optimization that improves skills over successive cycles
- Capsule system for bundling related Genes into reusable packages
- MCP and A2A protocol support for multi-agent interoperability
- Node.js-based with a fast CLI for interactive evolution runs

## Comparison with Similar Tools
- **GenericAgent** — task-driven skill trees; Evolver uses GEP for population-based optimization
- **AutoGPT** — action loops; Evolver focuses on skill improvement over time
- **DSPy** — prompt optimization; Evolver optimizes executable skill code
- **LangChain** — chain composition; Evolver evolves the chains themselves

## FAQ
**Q: What is Gene Expression Programming?**
A: A form of evolutionary computation where programs (Genes) are evolved through selection, crossover, and mutation to improve their fitness on a given task.

**Q: Is the evolution auditable?**
A: Yes. Every mutation, selection, and fitness evaluation is recorded as an Event with full provenance tracking.

**Q: Can I seed Evolver with existing skills?**
A: Yes. Import existing skill definitions as initial Genes to accelerate evolution.

**Q: Which agent frameworks integrate with Evolver?**
A: Any framework supporting MCP or A2A protocols, plus direct Node.js API integration.

## Sources
- https://github.com/EvoMap/evolver


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Source: https://tokrepo.com/en/workflows/asset-1b91ed23
Author: Script Depot