---
title: "agent-learning-kit vs autogen"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/future-agi-agent-learning-kit-vs-microsoft-autogen"
tools: ["future-agi-agent-learning-kit", "microsoft-autogen"]
---

# agent-learning-kit vs autogen

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick agent-learning-kit when license: agent-learning-kit is Apache-2.0, autogen is CC-BY-4.0; pick autogen when license: autogen is CC-BY-4.0, agent-learning-kit is Apache-2.0.

[agent-learning-kit](https://futureagi.com) reports 113 GitHub stars, 42 forks, and 4 open issues, last pushed Jun 30, 2026. [autogen](https://microsoft.github.io/autogen/) has 60k stars, 9.0k forks, and 945 open issues, last pushed Apr 15, 2026. Figures are from public GitHub metadata via [agent-learning-kit's repository](https://github.com/future-agi/agent-learning-kit) and [autogen's repository](https://github.com/microsoft/autogen).

| | [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) | [autogen](/tools/microsoft-autogen.md) |
| --- | --- | --- |
| Tagline | Evaluation Framework for all your AI related Workflows | A programming framework for agentic AI |
| Stars | 113 | 59,658 |
| Forks | 42 | 8,983 |
| Open issues | 4 | 945 |
| Language | Python | Python |
| Adopt for | - | AutoGen is a Python-based framework for developing and managing agentic AI systems. It includes the AutoGen Studio for no-code GUI setup, integrating with various models. |
| Persona | - | - |
| Runtime | - | - |
| License | Apache-2.0 | CC-BY-4.0 |
| Categories | AI Agents, Model Training, Vector Databases | AI Agents, LLM Frameworks |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) | [autogen](/tools/microsoft-autogen.md) |
| --- | --- | --- |
| Maintenance | Active (82%) | Steady (60%) |
| Days since push | 11d | 87d |
| Open issues (now) | 4 | 945 |
| Full report | [trust report](/tools/future-agi-agent-learning-kit/trust.md) | [trust report](/tools/microsoft-autogen/trust.md) |

## Shared compatibility

- **Python**: [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) - Python runtime; [autogen](/tools/microsoft-autogen.md) - Python runtime

## Decision facts: autogen

- **Requirements:** Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure.
- **Adopt for:** AutoGen is a Python-based framework for developing and managing agentic AI systems. It includes the AutoGen Studio for no-code GUI setup, integrating with various models.

## Choose when

### Choose agent-learning-kit if…

- License: agent-learning-kit is Apache-2.0, autogen is CC-BY-4.0.
- Tags unique to agent-learning-kit: agentic-ai, ai-agents, cicd, evaluation.
- Also covers Model Training, Vector Databases.

### Choose autogen if…

- License: autogen is CC-BY-4.0, agent-learning-kit is Apache-2.0.
- Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure..
- Tags unique to autogen: agentic-agi, agents, autogen, autogen-ecosystem.
- Also covers LLM Frameworks.
- You need a framework that supports integration with multiple AI models via OpenAI's chat completion client.

## When NOT to use agent-learning-kit

- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

## When NOT to use autogen

- If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework.
- When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited.
- You need solutions which do not involve additional installations for server components such as `playwright/mcp`, as AutoGen requires this setup for certain functionalities.

## Common questions

### What is the difference between agent-learning-kit and autogen?

agent-learning-kit: Evaluation Framework for all your AI related Workflows. autogen: A programming framework for agentic AI. See the comparison table for live GitHub stats and shared categories.

### When should I choose agent-learning-kit over autogen?

Choose agent-learning-kit over autogen when License: agent-learning-kit is Apache-2.0, autogen is CC-BY-4.0; Tags unique to agent-learning-kit: agentic-ai, ai-agents, cicd, evaluation; Also covers Model Training, Vector Databases.

### When should I choose autogen over agent-learning-kit?

Choose autogen over agent-learning-kit when License: autogen is CC-BY-4.0, agent-learning-kit is Apache-2.0; Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure.; Tags unique to autogen: agentic-agi, agents, autogen, autogen-ecosystem; Also covers LLM Frameworks; You need a framework that supports integration with multiple AI models via OpenAI's chat completion client.

### When should I avoid agent-learning-kit?

AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

### When should I avoid autogen?

If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework. When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited. You need solutions which do not involve additional installations for server components such as `playwright/mcp`, as AutoGen requires this setup for certain functionalities.

### Is agent-learning-kit or autogen more popular on GitHub?

autogen has more GitHub stars (59,658 vs 113). Stars measure visibility, not whether either tool fits your constraints.

### Are agent-learning-kit and autogen open source?

Yes - both are open-source projects on GitHub (agent-learning-kit: Apache-2.0, autogen: CC-BY-4.0).

### Where can I find alternatives to agent-learning-kit or autogen?

GraphCanon lists graph-backed alternatives at [agent-learning-kit alternatives](/tools/future-agi-agent-learning-kit/alternatives) and [autogen alternatives](/tools/microsoft-autogen/alternatives) ([agent-learning-kit markdown twin](/tools/future-agi-agent-learning-kit/alternatives.md), [autogen markdown twin](/tools/microsoft-autogen/alternatives.md)), ranked by typed relationship edges rather than popularity votes.

### Is there a machine-readable version of this comparison?

Yes. The markdown twin at [this comparison](/compare/future-agi-agent-learning-kit-vs-microsoft-autogen.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, agent-learning-kit or autogen?

agent-learning-kit: Active. autogen: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

### Where are the full trust reports for agent-learning-kit and autogen?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-learning-kit trust report](/tools/future-agi-agent-learning-kit/trust); [autogen trust report](/tools/microsoft-autogen/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=future-agi-agent-learning-kit`](/api/graphcanon/graph?tool=future-agi-agent-learning-kit)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_
