We welcome contributions from the community. Here's how you can help:
The easiest way to suggest a project is to open an issue using the project submission template.
Projects should meet the following criteria:
- Relevant: Directly related to AI Agent self-evolution, memory systems, A2A/MCP protocols, agent coding, prompt optimization, agent safety, or embodied AI. Multi-agent orchestration and swarm frameworks belong in awesome-agent-swarm
- Active: Has received commits within the last 6 months
- Open source: Source code is publicly available
- Documented: Has a README with clear description and usage instructions
- Minimum traction: At least 50 GitHub stars (exceptions for novel/unique projects)
- Fork this repository
- Add the project to
data/projects.jsonfollowing the schema below - Run
node scripts/generate-readme.jsto regenerate the README - Submit a pull request with a brief description of the project
Each entry in data/projects.json should follow this format:
{
"name": "Project Name",
"repo": "owner/repo",
"description": "One-line description of the project",
"category": "evolution|memory|protocols|platforms|coding|prompt-optimization|safety|embodied|community",
"maintainer": "github-username",
"tags": ["tag1", "tag2", "tag3"],
"stars": 0,
"paper": "https://arxiv.org/abs/... (optional)"
}| Category | Description |
|---|---|
evolution |
Agent self-evolution and self-improvement |
memory |
Memory systems for persistent agent cognition |
protocols |
A2A, MCP, and inter-agent communication protocols |
platforms |
Agent development and deployment platforms |
coding |
Agent coding and software engineering tools |
prompt-optimization |
Prompt and behaviour optimization frameworks |
safety |
Agent safety, guardrails, and alignment |
embodied |
Embodied AI, robotics, and device control |
community |
Community resources, learning materials, and surveys |
Use 2-3 descriptive tags per project. Reuse existing tags where possible:
autonomous self-evolving self-improving production-ready mcp a2a
multi-agent orchestration research lightweight open-source
To suggest a research paper, either:
- Open an issue describing the paper and its contribution
- Submit a PR adding the paper to the appropriate table in README.md
Papers should be:
- Published in a recognized venue (top conferences, journals, or notable arXiv preprints)
- Directly related to agent evolution, memory, multi-agent systems, or related topics
- Accompanied by a one-line description of the key contribution
| Script | Purpose |
|---|---|
node scripts/generate-readme.js |
Regenerate README.md from projects.json |
node scripts/update-stars.js |
Fetch latest star counts from GitHub |
node scripts/check-links.js |
Validate all repository links |
bash scripts/search-repos.sh [query] |
Search GitHub for relevant projects |
Be respectful. Provide constructive feedback. Help build a useful resource for the AI Agent community.