--- title: "autogen vs code2prompt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/microsoft-autogen-vs-mufeedvh-code2prompt" tools: ["microsoft-autogen", "mufeedvh-code2prompt"] --- # autogen vs code2prompt *GraphCanon updated Jul 11, 2026* ## Verdict Pick autogen when autogen is primarily Python; code2prompt is Rust; pick code2prompt when code2prompt is primarily Rust; autogen is Python. [autogen](https://microsoft.github.io/autogen/) reports 60k GitHub stars, 9.0k forks, and 945 open issues, last pushed Apr 15, 2026. [code2prompt](https://code2prompt.dev) has 7.5k stars, 426 forks, and 18 open issues, last pushed Jun 29, 2026. Figures are from public GitHub metadata via [autogen's repository](https://github.com/microsoft/autogen) and [code2prompt's repository](https://github.com/mufeedvh/code2prompt). | | [autogen](/tools/microsoft-autogen.md) | [code2prompt](/tools/mufeedvh-code2prompt.md) | | --- | --- | --- | | Tagline | A programming framework for agentic AI | A CLI tool to convert your codebase into a single LLM prompt with source tree, prompt templating, and token counting. | | Stars | 59,658 | 7,467 | | Forks | 8,983 | 426 | | Open issues | 945 | 18 | | Language | Python | Rust | | 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 | CC-BY-4.0 | MIT | | Categories | AI Agents, LLM Frameworks | Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [autogen](/tools/microsoft-autogen.md) | [code2prompt](/tools/mufeedvh-code2prompt.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Active (82%) | | Days since push | 87d | 11d | | Open issues (now) | 945 | 18 | | Owner type | Organization | User | | Full report | [trust report](/tools/microsoft-autogen/trust.md) | [trust report](/tools/mufeedvh-code2prompt/trust.md) | ## 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 autogen if… - autogen is primarily Python; code2prompt is Rust. - License: autogen is CC-BY-4.0, code2prompt is MIT. - 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 AI Agents. - You need a framework that supports integration with multiple AI models via OpenAI's chat completion client. ### Choose code2prompt if… - code2prompt is primarily Rust; autogen is Python. - License: code2prompt is MIT, autogen is CC-BY-4.0. - Tags unique to code2prompt: claude, cli, command-line, command-line-tool. - Also covers Developer Tools. ## 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. ## When NOT to use code2prompt - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between autogen and code2prompt? autogen: A programming framework for agentic AI. code2prompt: A CLI tool to convert your codebase into a single LLM prompt with source tree, prompt templating, and token counting.. See the comparison table for live GitHub stats and shared categories. ### When should I choose autogen over code2prompt? Choose autogen over code2prompt when autogen is primarily Python; code2prompt is Rust; License: autogen is CC-BY-4.0, code2prompt is MIT; 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 AI Agents; You need a framework that supports integration with multiple AI models via OpenAI's chat completion client. ### When should I choose code2prompt over autogen? Choose code2prompt over autogen when code2prompt is primarily Rust; autogen is Python; License: code2prompt is MIT, autogen is CC-BY-4.0; Tags unique to code2prompt: claude, cli, command-line, command-line-tool; Also covers Developer Tools. ### 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. ### When should I avoid code2prompt? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is autogen or code2prompt more popular on GitHub? autogen has more GitHub stars (59,658 vs 7,467). Stars measure visibility, not whether either tool fits your constraints. ### Are autogen and code2prompt open source? Yes - both are open-source projects on GitHub (autogen: CC-BY-4.0, code2prompt: MIT). ### Where can I find alternatives to autogen or code2prompt? GraphCanon lists graph-backed alternatives at [autogen alternatives](/tools/microsoft-autogen/alternatives) and [code2prompt alternatives](/tools/mufeedvh-code2prompt/alternatives) ([autogen markdown twin](/tools/microsoft-autogen/alternatives.md), [code2prompt markdown twin](/tools/mufeedvh-code2prompt/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/microsoft-autogen-vs-mufeedvh-code2prompt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autogen or code2prompt? autogen: Steady. code2prompt: Active. 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 autogen and code2prompt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autogen trust report](/tools/microsoft-autogen/trust); [code2prompt trust report](/tools/mufeedvh-code2prompt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=microsoft-autogen`](/api/graphcanon/graph?tool=microsoft-autogen) - 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/_