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.
MCP Server Orchestration: 3 MCP Servers, one intelligent agent
Connect Jira Service Management, Confluence and Google Sheets MCP servers 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 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.
- Jira Service Management Jsm, Confluence & Google Sheets 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.
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 MCP Server Orchestration
Which MCP servers 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 MCP servers 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?
MCP servers 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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MCP servers used in this workflow
Jira Service Management (JSM)
Jira Service Management (JSM) MCP Server connects your AI client to your service desk data. It lets you read customer requests, check queue status, list service desks, and search knowledge bases directly via the Jira JSM API. Use it to automate IT support tasks, triage tickets, or pull up deep details on any service inquiry.
Confluence
Confluence MCP Server lets your AI agent search, read, and write to your company wiki. You can query technical documentation, find HR policies, and publish formatted pages directly from your chat window. It connects your AI client to your Atlassian Confluence workspace.
Google Sheets
Google Sheets MCP Server lets your AI client read, write, and manage data directly in Google Sheets. Use conversational commands to pull data from specific ranges, append new rows, or structure entire spreadsheets. It acts as an analyst, letting you manipulate complex data without opening the GUI or writing formulas.