We built OneCLI because AI agents are being given raw API keys. And it's going about as well as you'd expect. We figured the answer isn't "don't give agents access," it's "give them access without giving them secrets."OneCLI is an open-source gateway that sits between your AI agents and the services they call. You store your real credentials once in OneCLI's encrypted vault, and give your agents placeholder keys. When an agent makes an HTTP call through the proxy, OneCLI matches the request by host/path, verifies the agent should have access, swaps the placeholder for the real credential, and forwards the request. The agent never touches the actual secret. It just uses CLI or MCP tools as normal.Try it in one line: docker run --pull always -p 10254:10254 -p 10255:10255 -v onecli-data:/app/data ghcr.io/onecli/onecliThe proxy is written in Rust, the dashboard is Next.js, and secrets are AES-256-GCM encrypted at rest. Everything runs in a single Docker container with an embedded Postgres (PGlite), no external dependencies. Works with any agent framework (OpenClaw, NanoClaw, IronClaw, or anything that can set an HTTPS_PROXY).We started with what felt most urgent: agents shouldn't be holding raw credentials. The next layer is access policies and audit, defining what each agent can call, logging everything, and requiring human approval before sensitive actions go through.It's Apache-2.0 licensed. We'd love feedback on the approach, and we're especially curious how people are handling agent auth today.GitHub: https://github.com/onecli/onecli Site: https://onecli.sh
FL score
out of 100
Verdict
high confidence
Competition
12
competitors found, emerging market, funded players
Trend
No signal yet
A Rust-based open-source vault and proxy for AI agents to securely manage API keys, addressing a critical pain point in a crowded, well-funded market.
The pain
The gap
Build angle
Strengths
Questions about this idea?
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Risks
Next steps
Fly Labs Method
Is the pain real, is there a gap, is it the right time, can one person build it.
High problem clarity and urgency, but the market is crowded with strong, funded players and similar open-source proxies, making a significant gap for a solo builder hard to carve out without a clear monetization path.
Value Equation
Dream outcome and how likely it feels, against the time and effort it costs.
Strong market need and timing, but weak differentiation and difficult monetization in a highly competitive landscape for a solo builder.
One-Person Business
Curiosity pull, identity fit, and a path from free value to paid for a solo creator.
Strong problem and creator fit, but monetization in a competitive enterprise market for an open-source tool presents a major hurdle for a solo builder.
Viral Frameworks
Hook strength, shareability, and how cheaply it can be tested.
Clear value proposition for a specific audience, but the open-source business model is currently undefined, and validation is needed for commercial viability in a highly competitive market.
Builder Lens
Evidence the problem exists, timing, defensibility, and a model that fits on a napkin.
Addresses a real, desperate problem with a narrow, deployable solution, and is well-positioned for future growth in AI agent security.
Why this verdict
Five lenses, one composite. How scoring works
The angle
This weekend
Who is already there, emerging market
Oasis Security provides an agentic access management (AAM) platform focused on governing how AI agents and machine identities access critical systems.
Pricing: Not publicly available, likely enterprise-focused with custom pricing.
Akeyless offers an identity security platform for machines, AI agents, and humans, providing secrets management, secretless authentication, and workload identity federation.
Pricing: Not publicly available, likely enterprise-focused with custom pricing. Mentions a 'Start Free' option for a demo.
CyberArk's solution discovers AI agents, enriches them with context, enforces least privilege access, and manages their lifecycle for comprehensive identity security.
Pricing: Not publicly available, likely enterprise-focused with custom pricing.
1Password Unified Access is a new agent security platform enabling organizations to securely deploy AI agents and automated workflows with credential, secret, and machine identity control.
Pricing: Unified Access Pro is generally available. Pricing not publicly listed; likely targets enterprise.
Agent Gateway is a security layer that proxies LLM/agent traffic, preventing agents from directly seeing sensitive credentials and enforcing outbound network policies.
Pricing: Not publicly available.
Sage is an open-source tool that inserts an interception layer between an AI agent and its operations (shell commands, URL fetches, file writes), checking each action.
Pricing: Free (open-source).
Token Security offers intent-based AI agent security, governing autonomous agents by aligning permissions with their intended purpose.
Pricing: Not publicly available.
Manifold is an AI Detection and Response (AIDR) platform securing autonomous AI on endpoints.
Pricing: Not publicly available.
Okta for AI Agents provides an identity layer for visibility and governance, including API Access Management and Privileged Credential Management, for AI agents.
Pricing: Available in Early Access. Pricing not publicly available.
Cencurity is a security gateway that proxies LLM/agent traffic, detecting, masking, and blocking sensitive data and risky code patterns while logging all activity.
Pricing: Not publicly available.
Cisco's A2A Scanner is an open-source security framework that validates agent identities and inspects their communications for threats like impersonation and prompt injection.
Pricing: Free (open-source).
Auth0's Token Vault is designed for securely storing and managing tokens for third-party services, allowing AI agents to call external APIs without direct exposure to raw API keys.
Pricing: Not publicly available; part of the Auth0 platform.
What they charge
Recent news
Open-source tool Sage puts a security layer between AI agents and the OS
Help Net Security, March 09 2026
Oasis Security raises $120m Series B for AI agent access
RegTech Analyst, March 20 2026
1Password Launches Unified Access for AI Agent Security
1Password, March 17 2026
Manifold Announces $8 Million Seed Funding Round to Secure Autonomous Endpoint AI Agents at Runtime
GlobeNewswire, March 18 2026
Token Security Introduces Intent-Based Security for AI Agents
GlobeNewswire, March 18 2026
Market signals
The market for securing AI agents is rapidly growing and receiving significant investment. Recent funding rounds, like Oasis Security's $120M Series B, highlight the increasing recognition of the critical need for specialized identity and access management solutions for autonomous AI. The industry is moving beyond traditional human-centric security models to address the unique challenges posed by non-deterministic AI agents and their access to sensitive systems.
What frustrates people
Last summer we faced a conundrum at my company, Tiger Data, a Postgres cloud vendor whose main business is in timeseries data. We were trying to grow our business towards emerging AI-centric workloads and wanted to provide a state-of-the-art hybrid search stack in Postgres. We'd already built pgvectorscale in house with the goal of scaling semantic search beyond pgvector's main memory limitations. We just needed a scalable ranked keyword search solution too.The problem: core Postgres doesn't provide this; the leading Postgres BM25 extension, ParadeDB, is guarded behind AGPL; developing our own extension appeared daunting. We'd need a small team of sharp engineers and 6-12 months, I figured. And we'd probably still fall short of the performance of a mature system like Parade/Tantivy.Or would we? I'd be experimenting long enough with AI-boosted development at that point to realize that with the latest tools (Claude Code + Opus) and an experienced hand (I've been working in database systems internals for 25 years now), the old time estimates pretty much go out the window.I told our CTO I thought I could solo the project in one quarter. This raised some eyebrows.It did take a little more time than that (two quarters), and we got some real help from the community (amazing!) after open-sourcing the pre-release. But I'm thrilled/exhausted today to share that pg_textsearch v1.0 is freely available via open source (Postgres license), on Tiger Data cloud, and hopefully soon, a hyperscalar near you:https://github.com/timescale/pg_textsearchIn the blog post accompanying the release, I overview the architecture and present benchmark results using MS-MARCO. To my surprise, we were not only able to meet Parade/Tantivy's query performance, but exceed it substantially, measuring a 4.7x advantage on query throughput at scale:https://www.tigerdata.com/blog/pg-textsearch-bm25-fu
AI
Hi HN!I recently switched from a Fedora/GNOME laptop to a MacBook Air. My old setup served me well as a portable workstation, but I’ve started traveling more while working remotely and needed something with similar performance but better battery life. The main thing I missed was a simple taskbar that shows the windows in the current workspace instead of a Dock that mixes everything together.I built boringBar so I would not have to use the Dock. It shows only the windows in the current Space, lets you switch Spaces by scrolling on the bar, and adds a desktop switcher so you can jump directly to any Space. You can also hide the system Dock, pin apps, preview windows with thumbnails, and launch apps from a searchable menu (I keep Spotlight disabled because for some reason it uses a lot of system resources on my machine).I’ve been dogfooding it for a few months now, and it finally felt polished enough to share.It’s for people who like macOS but want window management to feel a bit more like GNOME, Windows, or a traditional taskbar. It’s also for people like me who wanted an easier transition to macOS, especially now that Windows feels increasingly user-hostile.I’d love feedback on the UX, bugs, and whether this solves the same Dock/Spaces pain for anyone else.P.S. It might also appeal to people who feel nostalgic for the GNOME 2 desktop of yore. I started my Linux journey with it, and boringBar brings back some of that feeling for me.
AI
### Describe the project you are working on Godot C# bindings ### Describe the problem or limitation you are having in your project For the past weeks, I've been discussing with several Unity users intending to move to Godot C# regarding dealing with the C# garbage collector. The most common complaint I hear from users is that, in Unity, allocations can trigger unexpected GC spikes into the game. In Godot, we target to make all of the high performance APIs (those that intended to be called every frame) not allocate any memory, so theoretically the GC should not be a problem. Additionally, Godot starting from 4.0, uses the Microsoft CoreCLR version of .net, which also supposedly has a better garbage collector than Unity. But in all, after several discussions with Unity users, neither is enough reassurance for them, and they would really feel safer if Godot exposed a zero allocation API. ### Describe the feature / enhancement and how it helps to overcome the problem or limitation The idea of this proposal is that Godot exposes zero allocation versions of many functions in the C# API, that users can use if they desire. Technically, this could be done from the binding generator itself, without breaking compatibility, and without doing any modification to Godot itself. ### Describe how your proposal will work, with code, pseudo-code, mock-ups, and/or diagrams **WARNING** I am not familiar with C#, so take this as pseudocode. Imagine you have two functions exposed as to C#: ```C# void MyClass.SetArray( Vector2[] array); Vector2[] MyClass.GetArray(); ``` This works and is pretty and intuitive. However, it has two problems: * GC is allocated on return * Memory is copied to Godot native formats every time there is a call. The idea is to add NoAlloc versions, which can be generated directly by the binder automatically when required: ```C# void MyClass.SetArrayNoAlloc( Godot.Collections.PackedVector2Array array); void MyCl
AI