Securely scale AI usage across your organization. A single stack to Connect, Secure, Observe and Distribute agents, MCPs, and Skills within your company.
This week focused on expanding the Platform MCP's capabilities for managing plugins and skill suggestions. The team shipped workflows to review, approve, and dismiss skill suggestions, republish stale plugins, and display a plugin's last publish attempt. Alongside this, infrastructure improvements…
Get this in your inbox every Monday →A deterministic 0–100 hygiene score — README, license, CI, tests, docs, and freshness.
Who ships this repo — author concentration and the bus factor across the last 300 mainline commits.
How welcoming this repo is to contributors — issue throughput, close time, responsiveness, and good-first-issue count.
What this project is built on — dependency count by ecosystem, the license mix, and anything worth a legal look before you adopt it.
Whether this project's CI can be trusted — pass rate, run times, flaky runs, and which workflow is the weak link.
Grounded in gram's README, structure, and recent commits — answers won't invent code they haven't seen.
A Monday email with what shipped, in plain English — no account needed.
Showing raw commit titles for the newest commits. Sign in to generate AI summaries.
feat: add a dashboards API to create, lay out, filter and copy dashboards (#7173)
fix: name the mismatched resource when protected resource metadata is rejected (#7192)
feat: risk event detail drawer with full MCP tool-call payload reveal (#7071)
feat: validate MCP 2026-07-28 request metadata and reserve standard MCP headers (#7155)
A floor, not a guess: counts only commits whose author, co-author trailer, or message explicitly credits an AI tool (Claude, Copilot, Cursor, aider, Codex…). Based on 30 mainline commits. Unattributed AI code isn't counted here — the full audit estimates that separately.
