Turn Support Tickets Into KB Articles via MCP.
Your support team answered 'how to reset my password' 340 times this quarter , each time a $65/hour agent spent 8 minutes writing the same answer because nobody turned the first answer into a knowledge base article
Works with every AI agent you already use
…and any MCP-compatible client
Waiting for input…
Gemini How It Works
Your AI agent reads all resolved tickets from Jira Service Management: the question, the resolution, the request type, and how many times similar tickets appeared.
It groups tickets by topic and identifies repeat questions: 'How to reset password: 340 tickets. How to export data: 189 tickets.
How to add team members: 156 tickets.' For each repeat question, the agent checks Confluence: does an article exist? If not, it takes the best resolution from JSM , the one that resolved fastest with the highest satisfaction rating , and creates a Confluence article.
The Google Sheet tracks the impact: 'Password reset article created June 1. Tickets before: 85/month. Tickets after (projected from first 2 weeks): 23/month.
Deflection rate: 73%. Agent time saved: 8.2 hours/month. Cost savings: $533/month from one article.' The knowledge base writes itself from the answers your team already gave.
Connector Orchestration: 3 Connectors, one intelligent agent
Connect Jira Service Management, Confluence and Google Sheets Connectors so your AI agent reads resolved support tickets from JSM, identifies repeated questions, checks whether a Confluence knowledge base article exists for each topic, and creates new articles from the best resolved answers. Support teams where agents answer the same questions hundreds of times , while the knowledge base sits empty because creating articles is 'on the backlog' and nobody has time , get a system that automatically converts the best support answers into searchable, self-service documentation.
Jira Service Management Jsm
triggerReads resolved tickets, request types, resolution descriptions and frequency patterns
list_requests get_request list_request_types list_queues Confluence
actionCreates and updates knowledge base articles from the best support resolutions
create_page search_confluence list_pages list_spaces Google Sheets
actionTracks ticket frequency, knowledge gaps and deflection rate improvements
append_sheet_values update_sheet_values create_spreadsheet get_spreadsheet 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 Connector
Convert any internal API into a Connector. 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 each 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.
- Jira Service Management Jsm, Confluence & Google Sheets ready in the catalog right now
- Add more from 5,800+ servers whenever you need
- Connections are secured and compliant by default
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers and recipes added weekly
Superpowers you didn't know your AI had
The Vinkius catalog gives your agent access to 5,800+ Connectors and the intelligence to combine them. Imagine never logging into another dashboard. Your AI handles the work across all tools, in one conversation. That's what this connectivity layer 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 all platforms.
Contextual Reasoning
Each 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 Connectors once, and your agent handles the rest. Each time, without intervention.
Made for
exactly this
Your AI agent taps into the entire Vinkius AI Connectors to handle these for you. You describe what you need. It does the rest.
Support managers who want to automatically convert resolved tickets into searchable knowledge base articles
Customer success teams tracking deflection rates to prove the value of self-service documentation
Operations leaders quantifying the cost of not having a knowledge base in agent hours and dollars
Product teams using support ticket frequency data to identify UX problems that generate unnecessary support load
Frequently Asked Questions About This Connector Orchestration
Which Connectors do I need for this workflow?
Three: Jira Service Management, Confluence and Google Sheets. Connect all three to your AI client before running any prompt from this page.
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. Connect the Connectors and paste a prompt.
Does the agent overwrite existing Confluence articles?
No. The agent checks for existing articles first. If one exists, it reports whether it is stale and suggests updates. It only creates new articles for topics with no existing documentation.
Is my support data secure?
Connectors authenticate through API keys. JSM and Confluence data stays in your Atlassian account. The Google Sheet is in your Drive. Vinkius does not store your support tickets or knowledge base content.
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Connectors used in this workflow
Jira Service Management (JSM)
Jira Service Management (JSM) MCP lets your AI agent manage service desks, customer requests, and support queues. It connects directly to your Jira JSM instance so your agent can pull ticket details, browse knowledge bases, and monitor organizational data without you having to switch tabs.
Confluence
Confluence MCP. Let your AI agent read, search, and create wiki pages in your Atlassian workspace. It turns your organization's knowledge base into a searchable, actionable resource for your agent.
Google Sheets
Google Sheets MCP lets you read, write, and manage spreadsheet data through your AI agent. Stop wasting time on manual data entry or complex formulas. Just tell your agent to pull specific ranges, add new rows, or create entire new sheets on the fly. It handles the tedious work of keeping your data organized so you can focus on making decisions.