Most MCP servers look up a ticket. DevStride delivers the work.
Point your agent at a typical project-tool MCP and it looks up a ticket. Point it at DevStride and it assesses risk, drafts the change, plans the whole build, then applies it the moment you say go. Same protocol. A different class of partner.
The same loop, whatever the work.
Whether you ship a product or deliver for clients, the pattern is identical: the MCP Server does the legwork, you make the calls.
- Scope a client engagement into a plan the whole team can see.
- Spot an at-risk milestone and reallocate to protect the date.
- Turn out a polished, client-ready status update every week.
- Draft the plan, then run the delivery loop story by story.
- Surface what's slipping and rebalance to hit the release.
- Draft the sprint status for stakeholders, ready to review and send.
Beyond read-only. Beyond light edits.
Most MCP integrations stop at read and light edits. DevStride goes a level further, and the judgment stays with you.
An agent can see your data and answer questions about it.
An agent can nudge a field, change a status, or post an update.
Assesses risk, drafts the plan, applies the change you approve. The work a delivery lead does, with you still making the call.
It does the work a delivery lead would hand off. You stay the delivery lead.
It proposes. You approve. It applies.
Your agent works with your permissions. It proposes, you approve, it applies. Most MCP integrations stop at read and light edits; DevStride's assesses risk, proposes changes, even drafts whole plans.
Assess
AI pulls the portfolio, traces dependency chains, and surfaces what's trending late.
You decide what actually matters.
Modify
AI drafts a rebalance and shows which items move and who picks up the load.
You review the proposal and give the go-ahead.
Create
AI drafts a full plan: parent items, child work, boards, and the dependency stack.
You vet and refine the plan.
Plan with AI. Deliver on a loop. Keep the judgment.
AI does the smart grunt work. People make the judgment calls.
We planned and shipped our own Service Desk through this MCP, every item tied to the change that built it.
Using the DevStride MCP Server, our team had an agent draft the entire build: the parent item, the child work, the boards, and the full dependency stack. We vetted the plan, then execution backfilled against it.
Every item links to the change that implemented it, in order. Someone with zero context can see exactly what happened, why, and when. That's the organizational memory you get when your AI partner works inside the all-in-one delivery platform where humans and AI work together.
Heavy hitter. Light lift.
No glue code, no infrastructure to stand up. The MCP Server is built on the same API that powers the app, so your assistant can reach nearly everything you can do in the product. Connect in minutes from the Connect AI page.
Open Connect AI
Start from the Connect AI page in the DevStride app and pick the client you already use.
Sign in securely
Authorize with OAuth 2.1. The connection works with your DevStride permissions, so treat it like your own credentials.
Start working
Ask your agent to assess, propose, or draft. You approve from there.
Works with Claude, ChatGPT, Cursor, Copilot, Codex, and Gemini CLI, plus any MCP-compatible client. Your AI tool's subscription (Claude, Claude Code, etc.) is billed separately by that provider.