CLI-Anything — a framework for making any existing software agent-native, without modification

The premise is blunt: today's software is built for humans. Tomorrow's primary users will be agents. CLI-Anything, from the HKUDS lab, operationalizes that gap by turning any CLI tool into a structured, agent-ready interface — JSON output, self-describing --help docs, composable commands — all without touching the underlying software. 567 stars and 51 forks in under 24 hours.

The timing is right. Claude Code, Cursor, and Codex are already running thousands of real workflows through CLI daily. What CLI-Anything adds is the scaffolding to make that reliable at scale: deterministic, structured output instead of scraping human-readable text, self-documentation agents can discover without hand-holding, and a design philosophy that CLI is already the universal interface — it just needs to be agent-first.

If you're building agents that need to interact with legacy tooling, internal scripts, or any software that predates the LLM era, this is the most pragmatic path forward. The alternative is building custom MCP servers for everything. This is one command.

Evaluate Now. → https://github.com/HKUDS/CLI-Anything

mcp2cli — turn any MCP server or OpenAPI spec into a CLI at runtime, zero codegen — The HN thread has 66 comments and 102 points for a reason. MCP's token overhead is a real problem: 30 tools injecting their full schema every turn costs ~3,600 tokens before the model does anything. mcp2cli flips the model — tools get discovered on demand via CLI, dropping schema overhead by 96–99%. Ships with a skills.sh installable agent skill so Claude Code/Cursor/Codex can use it immediately. The combination with CLI-Anything makes today a strong CLI-as-agent-interface day. Evaluate Now. → https://github.com/knowsuchagency/mcp2cli

OpenMOSS — self-organizing multi-agent platform for autonomous team workflows — 172 stars, 30 hours old. Agents planning, executing, reviewing, and patrolling tasks with zero human intervention. The "patrol" concept — agents monitoring other agents — is the differentiator here. Most multi-agent frameworks stop at delegation; this one adds a watchdog layer. Worth understanding before the pattern becomes table stakes. Watch. → https://github.com/uluckyXH/OpenMOSS

arbor — native desktop app for agentic Git worktrees and diffs — 189 stars after 5 days. Agentic coding workflows have a dirty secret: they thrash your working tree. arbor solves this with a native macOS app purpose-built for managing multiple Git worktrees, terminals, and diffs simultaneously — the kind of context-switching that Cursor and Claude Code generate but don't manage. Early, but the category is real. Watch. → https://github.com/penso/arbor

agentlytics — analytics dashboard for AI coding agents — 152 stars. Covers Cursor, Windsurf, Claude Code, VS Code Copilot, Zed, and more. If you're running multiple agents across a team and want actual usage data — not vibes — this is currently the only consolidated dashboard doing it. 59 hours old. Evaluate Now. → https://github.com/f/agentlytics

Lucid — an intelligence layer grounding autonomous agents in verified, real-time knowledge

85 stars, 3 hours old at collection time. The pitch is narrow and useful: agents hallucinate not because they're bad at reasoning, but because their knowledge is stale or unverified. Lucid inserts a grounding layer that feeds real-time, verified facts at scale before the agent acts.

This is early — but the problem is increasingly the bottleneck for production agent deployments. As agentic systems take on higher-stakes decisions, the "confident but wrong" failure mode becomes a liability, not a quirk. Worth watching as a category, not just a repo.

→ https://github.com/get-Lucid/Lucid

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