Run Async Standups From Sprint Data Using MCP.
Sprint progress checked, PR blockers surfaced, standup notes generated, meeting prep done , run your daily standup in 30 seconds
Works with every AI agent you already use
…and any MCP-compatible client
Waiting for input…
Gemini How It Works
Your AI agent reads Linear: Sprint 24 has 18 issues, 11 completed, 4 in progress, 3 not started. Sprint is 68% through the time window but only 61% complete , slightly behind.
The 4 in-progress issues: PLT-891 'Auth MFA implementation' is blocked , waiting on design spec from Product. PAY-234 'Payment retry logic' is in review.
PRD-567 'Dashboard export' is in progress, on track. PRD-568 'Settings page redesign' is in progress, at risk (no PR opened yet).
The agent checks GitHub: 3 open PRs. PR #198 has been waiting for review for 2 days , no reviewer assigned.
PR #201 has 2 approvals, ready to merge. PR #203 has merge conflicts. The agent checks Google Calendar: @maria has 4 meetings today (3.5 hours blocked).
@carlos has no meetings , free for deep work. @sarah has a 2-hour product review at 14:00. It generates the standup: 'Sprint 24: 61% done, 68% time elapsed , 1 day behind target.
Blockers: PLT-891 waiting on design spec, PR #198 unreviewed for 2 days. Risks: PRD-568 has no PR with 3 days left.
Action: assign reviewer to PR #198, unblock PLT-891 design spec. Team availability: @carlos is free for pairing on PRD-568.'
MCP Server Orchestration: 3 MCP Servers, one intelligent agent
Connect Linear, GitHub and Google Calendar MCP servers so your AI agent pulls the current sprint status from Linear, cross-references open PRs and blockers from GitHub, checks the team's calendar for meeting conflicts, and generates a complete standup summary. Engineering teams spending 15-30 minutes every morning rehashing yesterday's work get a ready-to-go standup brief that highlights blockers, risks and today's priorities. No going around the room. No 'I forgot what I did yesterday.' One prompt and the standup runs itself.
Linear
triggerReads sprint progress, active issues and blocked tickets
list_issues list_cycles get_issue list_teams search_issues Github
actionChecks open PRs, review status and merge blockers
list_pull_requests get_repository_details list_repo_issues Google Calendar
actionReads team schedules to flag meeting-heavy days and conflicts
check_free_busy create_event get_calendar_metadata Run This Automation Today
Connect Claude, ChatGPT, Cursor, or any AI agent to the Vinkius catalog and run this automation in minutes.
Build Your Own MCP
Turn any internal API into an MCP server. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Connect & Automate
The 3 servers this recipe uses are ready in the catalog. Connect them once, paste a prompt, and your AI runs the full workflow.
- Linear, Github & Google Calendar ready in the catalog right now
- Add more from 4,700+ servers whenever you need
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers and recipes added every week
Superpowers you didn't know your AI had
The Vinkius catalog gives your agent access to 4,700+ MCP servers and the intelligence to combine them. Imagine never logging into another dashboard. Your AI handles the work across every tool, in one conversation. That's what this infrastructure was built for.
Cross-Platform Intelligence
Your agent doesn't just connect to tools. It understands the relationships between them. Data flows where it needs to go, automatically, with full context preserved across every platform.
Contextual Reasoning
Every decision your agent makes considers the full picture. It reads CRM data, checks calendars, reviews conversation history, and acts on everything at once. Not step by step. All at once.
Productivity at Scale
What used to take 45 minutes across five different dashboards now takes one sentence. Your agent runs the entire workflow end to end while you focus on decisions that actually matter.
Zero-Config Reliability
No API keys to paste. No webhooks to configure. No YAML to debug. Connect your MCP servers once, and your agent handles the rest. Every time, without intervention.
Made for
exactly this
Your AI agent taps into the entire Vinkius MCP catalog to handle these for you. You describe what you need. It does the rest.
Engineering teams who spend 15-30 minutes in daily standups and want a pre-generated brief that highlights only blockers and risks
Remote-first teams across time zones who need async standup reports delivered to a shared channel instead of synchronous meetings
Engineering managers who want sprint health metrics (velocity gap, PR aging, blocker count) without manually checking Linear and GitHub
Scrum masters who need automated sprint risk detection , at-risk tickets, stale PRs, unresolved blockers
Frequently Asked Questions About This MCP Server Orchestration
Which MCP servers do I need for this workflow?
Three: Linear, GitHub and Google Calendar. Connect all three to your AI client.
Does this work with Claude Desktop, Cursor or Windsurf?
Yes. Any AI client that supports the Model Context Protocol works , Claude Desktop, Cursor, Windsurf, Cline and others.
Can I use Jira instead of Linear?
Yes. Replace the Linear MCP server with the Jira Cloud MCP server. The agent reads sprint boards and issues from Jira instead.
Does it replace the standup meeting entirely?
It can replace the status-sharing portion. Many teams use the generated brief and keep a 5-minute discussion for blockers only, cutting 15-minute standups to 5 minutes.
How does it know which PRs correspond to which Linear tickets?
The agent matches PR titles and branch names against Linear issue IDs (e.g., PR branch 'plt-891-auth-mfa' matches Linear issue PLT-891).
Can I schedule this to run automatically every morning?
The workflow runs on-demand. To automate, trigger the prompt from a cron job or a morning Slack bot that calls your AI client.
Find API Vulnerabilities First Using MCP
Your OpenAPI spec has 14 security findings and 3 match active HackerOne reports , your agent creates the tickets before the bounty payout
Find Codebase Duplications Using MCP Servers
Your codebase has 4 different implementations of date formatting, 3 versions of the retry logic, and 2 competing validation libraries , but nobody knows because grep only finds exact matches and these duplicates are semantic
How MCP Servers Auto-Triage Bug Reports
New bugs detected, severity classified, sprint tickets created, team notified , triage your backlog without a standup
MCP Recipe to Fix Production Crashes Faster
Your app crashed 847 times yesterday and the error report sits in Honeybadger while your Linear board has no idea , the engineer who wrote the broken code merged a different PR today
MCP Recipe to Kill Codebase Bloat
Codebase audited, bloat identified, requirements questioned, lean tickets created , kill architectural complexity before it ships
MCP Servers for Multi-Client Sprint Management
Your dev team tracks their work in Linear but the PM reports to clients in ClickUp , which means every sprint update is manually transcribed between two tools, and by the time the client sees it in ClickUp the data is already outdated
MCP servers used in this workflow
Linear
Linear lets your AI client read, write, and manage issues directly inside Linear—no tab switching needed. You can list all teams, search for specific bugs, create new tasks with defined priorities, or add comments right from your IDE. It gives your agent full control over project metadata, allowing you to check sprint progress, view project scope, and audit issue status using natural conversation.
GitHub
GitHub MCP Server manages repositories, tracks issues, and searches code via AI agents. Connect your GitHub account to your preferred AI client and automate core developer workflows—listing repos, getting file contents, or creating new issues—all from a natural conversation. Manage your entire software development lifecycle without leaving your chat window.
Google Calendar
Google Calendar MCP Server manages your entire professional schedule. It lets your AI client read every meeting detail, check for time conflicts across multiple users, and book new appointments directly in chat. You can list all calendars, search past events by keyword, or completely modify an existing booking—all without touching the web interface.