head to head · open source
readme-ai vs MisakaNet
readme-ai has 3,006 GitHub stars, 296 forks, 57 open issues and last shipped 4 days ago. MisakaNet has 554 stars, 228 forks, 98 open issues and last shipped yesterday. readme-ai leads on adoption by 443% (3,006 vs 554 stars). readme-ai is written in Python under MIT; MisakaNet is written in Python under Apache-2.0. readme-ai has attracted 10% as many forks as stars, MisakaNet 41%. MisakaNet was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (ai-agents), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| readme-ai | MisakaNet | |
|---|---|---|
| GitHub stars | ★ 3.0K | ★ 554 |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-04 | 2026-11-07 |
| Forks | ⑂ 296 | ⑂ 228 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick readme-ai if
- You weight community size — 3.0K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick MisakaNet if
- You want the MisakaNet feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and MisakaNet fits your workflow better
About readme-ai
Designed for simplicity, customization, and developer productivity. The metrics above are rendered with HyperWeave — an experimental SVG artifact layer for agents. Explore → Quick Links Intro Demo Features Quickstart Configuration Example Gallery Contributing Guidelines [!IMPORTANT] Explore the [Official Documentation][docs] for a complete list of features, customization options, and examples. Introduction ReadmeAI is a developer tool that automatically generates README files using a robust repository processing engine and advanced language models. Simply provide a URL or path to your codebase, and a well…
read the full readme-ai overview →
About MisakaNet
English 日本語 简体中文 MisakaNet mcp name: io.github.Ikalus1988/misakanet Stop debugging the same error twice. MisakaNet searches 411+ failure lessons so an agent skips the bugs someone already paid for, instead of rediscovering them one session at a time. Agent native interfaces: MCP server (7 tools), WebMCP (browser navigator.modelContext ), llms.txt / llms full.txt , and A2A discovery through .well known/agent card.json . Core Install Ecosystem What is MisakaNet? Git backed failure memory for AI coding agents. An error shows up → the agent searches the lessons → it applies a fix somebody already verified → if…
read the full MisakaNet overview →
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Frequently asked questions
Is readme-ai or MisakaNet more popular?
readme-ai has 3,006 GitHub stars and MisakaNet has 554. readme-ai has the larger community by that measure.
Are readme-ai and MisakaNet free?
Both are open source. readme-ai is licensed under MIT and MisakaNet under Apache-2.0. Neither carries a licence fee.
What is the difference between readme-ai and MisakaNet?
readme-ai is written in Python and MisakaNet in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, readme-ai or MisakaNet?
Choose readme-ai if you want the larger community (3,006 stars) or its MIT licence terms. Choose MisakaNet if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.