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Ask Axify anything,
from inside Claude.
The Axify MCP server brings live engineering intelligence, DORA, cycle time, AI adoption, team health, into the AI tools your leaders already use. No more dashboard scavenger hunts.
The open standard for connecting AI to your tools.
The Model Context Protocol is the emerging standard that lets AI clients like Claude securely call into external systems on your behalf, through your permissions, not a back-channel.
The Axify MCP server exposes your engineering data, DORA, flow, AI adoption, team health, as a set of structured tools the AI client can call and reason over. Ask in natural language, get answers from live data.
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Open protocolAny MCP-compatible AI client works the same way.
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Permission-scopedInherits the access you already have in Axify.
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Composable toolsChain queries to answer questions a single dashboard can't.
Everything Axify shows you, available as a tool call.
V1 ships read-only. Write actions, scheduled workflows, and agentic operations are on the roadmap.
Deploy frequency, lead time for changes, change failure rate, MTTR, filterable by team and timeframe.
Cycle time, PR throughput, review time, rework, and quality across every team in your org.
Usage, confidence, habit, and consumption broken down by user, team, and tool.
List teams, list contributors, get details on any of them, the metadata Claude needs to chain queries.
One-call "weekly team summary" and "quarterly board summary" tools that return ready-to-paste narratives.
Tools chain. Ask compound questions that a single dashboard view can't answer; Claude does the joining.
Connect once. Query from anywhere.
Three steps from install to your first answer in Claude.
Connect Axify in your AI client
Add the Axify MCP server in Claude (or any MCP-compatible client). One OAuth flow links it to your Axify workspace.
Ask in natural language
Ask any question you'd ask the dashboard, and the harder ones a single view can't answer. Claude composes tool calls.
Get live answers, scoped to you
Axify pulls fresh data from Jira, GitHub, GitLab, Azure DevOps and your AI tools, scoped to your existing permissions.
Ask a question. Get a chart.
Claude calls the Axify MCP server, gets live data, and renders the answer as a visualization, not a wall of JSON.
get_team_summary()
ok
Payments had a strong week. 14 deploys (up 3) and cycle time dropped to 3.2 days.
One yellow flag: review time grew 7h → 9h. Want me to drill into which PRs are getting stuck?
compare_teams()
ok
Platform leads on AI adoption at 84%, and they're notably faster across the board. Their pattern is shorter PRs reviewed within the day. Worth a sync between the two EMs.
Built around the questions leaders actually ask.
Six scenarios drawn from CTO, VP, and EM workflows we already see in Axify.
Open Claude. Ask “How did we do last week?”. Get a narrative summary across DORA, cycle time, and AI adoption, ready to forward to the exec team.
Draft a board one-pager in Claude. Pull last quarter's DORA trends, AI adoption ROI, and team well-being deltas, and iterate the narrative without ever opening Axify.
“Which teams have the lowest cycle time but the lowest AI adoption?”, a query that joins three views. Claude composes the tool calls and returns one answer.
“How does my PR review time compare to the team average this sprint?”, answered in your editor, no context switch.
Ask for the last two-week delta on cycle time, rework, and review time. Walk into retro with talking points already written.
Coming after launch: have Claude post your weekly team summary to a channel every Monday at 9am, no human in the loop required.
Your data stays on your terms.
The MCP server inherits the access controls you've already set up. If you can't see a team in Axify, the AI client can't either, no exceptions.
Questions, answered.
Find answers to the most common questions about Axify MCP
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When will the Axify MCP server be available?
It's currently in private preview. Public launch is targeted for Q2 2026. Join the waitlist and we'll reach out as we open early access cohorts.
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Which AI clients are supported?
At launch: Claude Desktop, Claude Code, and Claude Web. Cursor and GitHub Copilot will follow shortly after. Any MCP-compatible client will work once we add it to the supported list.
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Will it have write access to my Axify workspace?
No, v1 is strictly read-only. Write actions (creating OKRs, posting alerts, leaving comments), scheduled workflows, and admin operations are on the post-launch roadmap and will be opt-in.
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How does it handle permissions?
The MCP server connects via OAuth and inherits your existing Axify role and team scope. If a teammate can't see a team in the Axify dashboard, the AI client they're using can't query that team's data either.
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What data sources does it pull from?
The same integrations that already power Axify: Jira, Azure DevOps, GitHub, GitLab, Bitbucket, and your AI-tool integrations (Copilot, Cursor, Claude, and Lite LLM). No new connectors required.
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Does it cost extra on top of my Axify subscription?
Pricing for the MCP server is being finalized. We'll share details with waitlist members ahead of public launch.
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Is it self-hostable?
At launch, the MCP server is hosted by Axify (so OAuth and updates are handled for you). We're evaluating self-hosted deployment as a follow-up. Let us know if it's a requirement for your org.
Be the first to ask Axify anything.
Join the waitlist for early access. We'll reach out as we open cohorts.