Manifold – generate CLI and MCP surfaces from one .NET operation

Hacker News

I built Manifold, an operation-first foundation for .NET. The idea is simple: define an operation once, then generate fast CLI and MCP surfaces from that single definition. I made it because I kept running into the same problem in real projects: the same capability needed to be exposed through multiple developer-facing surfaces, but the definitions, bindings, and runtime wiring kept drifting apart over time. Manifold focuses on: one handwritten operation definition as the source of truth source-generator-first design generated CLI bindings generated MCP tool metadata and invocation samples for CLI, MCP stdio, and MCP Streamable HTTP Repo: https://github.com/Garume/Manifold Release: https://github.com/Garume/Manifold/releases/tag/v1.0.0 Wiki: https://github.com/Garume/Manifold/wiki I’d especially love feedback on whether this API shape feels natural for .NET, and whether a foundation like this is useful for MCP-oriented tooling.

Visit product View on Hacker NewsMar 29, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: mcp, single · Missing: mac, agents, macos

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

25%25% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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