by AgentToolkit · MCP Server · ★ 94
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Evolve: On‑the‑job learning for AI agents Blog posts: IBM announcement | Hugging Face blog Coding agents repeat the same mistakes because they start fresh every session. Evolve gives agents memory — they learn from what worked and what didn't, so each session is better than the last. Evolve is a system designed to help agents improve over time by learning from their trajectories. The Lite version is designed to effortlessly slot into existing agent assistants like Claude Code and Codex. It uses a combination of an MCP server for tool integration, vector storage for memory, and LLM-based conflict resolution to refine its knowledge base. On the AppWorld benchmark, Evolve improved agent reliability by +8.9 points overall, wit
| Stars | 94 |
| Forks | 11 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 70.3553180589276/100 |
| Open Issues | 57 |
| Last Updated | 2026-07-02 |
| Created | 2025-12-12 |
| Platforms | claude-code, codex, mcp, python |
| Est. Tokens | ~15k |
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altk-evolve is Self improving agents through iterations. It is categorized as a MCP Server with 94 GitHub stars.
altk-evolve is primarily written in Python. It covers topics such as agent-learning, agent-memory, agentic-workflows.
You can find installation instructions and usage details in the altk-evolve GitHub repository at github.com/AgentToolkit/altk-evolve. The project has 94 stars and 11 forks, indicating an active community.
altk-evolve is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to altk-evolve on Agent Skills Hub include iai-personal-memory-engine, Ori-Mnemos, claude-emporium. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.