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UnoRouter

UnoRouter is an LLM API gateway for side project builders that turns a pile of provider accounts into a single OpenAI compatible key. Point any OpenAI SDK, Claude Code, Cline or a chat client at UnoRouter and you can call Claude, GPT, Gemini, DeepSeek, Qwen and other major models by changing only the model name. If a provider fails mid request, the call is retried on another healthy route, so your project keeps answering. Free models are available without a credit card, which suits prototypes and weekend builds. Paid models are billed per token at list prices, no subscription. The code is open source on GitHub, and the built in web chat stores conversations in your browser rather than on a server.

Developer Tools / AI & ML Infrastructure

0.0 (0)

SkaleAgents

SkaleAgents is a control plane for AI DevOps agents. Publish specialist agents, connect MCP from your IDE — one control plane for AI DevOps work. Public bots, prompts and review checks are free; paid Starter, Pro and Max plans are available for organizations.

Developer Tools / AI & ML Infrastructure

0.0 (0)

Vynaris

Vynaris hosts powerful uncensored models—including Qwen3.8-27B, DeepSeek-V4-Flash-0731, and Qwen3.6-35B-A3B—through an OpenAI-compatible API for authorized security testing and research.

Developer Tools / AI & ML Infrastructure

0.0 (0)

ContextDrop

ContextDrop is a persistent memory layer for AI-powered development. Tired of repeating the same project context, architecture decisions, and technical details every time you start a new AI conversation? ContextDrop helps developers organize reusable project memories and make them accessible to AI coding tools through MCP. Currently, you can connect ContextDrop to Cursor using a remote MCP server, retrieve your active project context, and search stored memories directly from your AI workflow. No more constantly copying and pasting the same project background into every conversation. We're building ContextDrop to make AI-assisted development more consistent across projects, sessions, and tools. Try it out and let us know what you think. 🌐 https://usecontextdrop.com

Developer Tools / AI & ML Infrastructure

0.0 (0)

Pramana

AI agents can’t be tested — the model answers differently every time, so there’s nothing stable to assert against. Teams change a prompt, ship it, and wait for a customer to complain. Pramana records every call your agent makes in production. You then re-run your new code against that recording: every model answer comes back exactly as it did the first time, so anything different is your change. It can’t reach the internet while it does this, so a recorded payment can’t fire twice — which makes it safe on every pull request. The same recording is signed and tamper-evident, so when someone asks what your AI actually did, you can prove it with a tool that never talks to our servers. Same recording. One is a test suite. The other is proof.

Developer Tools / AI & ML Infrastructure

5.0 (1)

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