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Vinkius

Atlassian (Jira & Confluence) MCP Server for Vercel AI SDK 9 tools — connect in under 2 minutes

Built by Vinkius GDPR 9 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Atlassian (Jira & Confluence) through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.

Vinkius supports streamable HTTP and SSE.

typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

async function main() {
  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      // Your Vinkius token — get it at cloud.vinkius.com
      url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    },
  });

  try {
    const tools = await mcpClient.tools();
    const { text } = await generateText({
      model: openai("gpt-4o"),
      tools,
      prompt: "Using Atlassian (Jira & Confluence), list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Atlassian (Jira & Confluence) MCP Server

Transform your Atlassian Jira and Confluence instance into a conversational command center for your AI agent. This integration bridges the gap between complex agile workflows and actionable intelligence, allowing your agent to audit Jira issues, manage active sprints, and retrieve deep knowledge from Confluence wikis through natural language. Whether you're tracking a bug's lifecycle or auditing enterprise documentation, your agent acts as a direct, real-time navigator across your Atlassian ecosystem, ensuring your team stays aligned and data-driven without manual dashboard hopping.

The Vercel AI SDK gives every Atlassian (Jira & Confluence) tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 9 tools through the Vinkius and stream results progressively to React, Svelte, or Vue components — works on Edge Functions, Cloudflare Workers, and any Node.js runtime.

What you can do

  • Jira Issues & Search — Search issues using complex JQL, view exact tickets, or manage epics and stories seamlessly through your agent.
  • Agile Boards & Sprints — List active boards, explore historical sprints, and get an overarching view of project health effortlessly.
  • Confluence Wikis & Pages — Search across enterprise documentation using CQL, list spaces, and extract the full textual content of rich wiki pages.
  • Project & Identity Oversight — Browse available projects and see the identity mappings of the current user automatically.
  • Knowledge Retrieval — Stream rendered HTML or textual properties of specific Confluence pages directly into your conversation context.

The Atlassian (Jira & Confluence) MCP Server exposes 9 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Atlassian (Jira & Confluence) to Vercel AI SDK via MCP

Follow these steps to integrate the Atlassian (Jira & Confluence) MCP Server with Vercel AI SDK.

01

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the script

Save to agent.ts and run with npx tsx agent.ts

04

Explore tools

The SDK discovers 9 tools from Atlassian (Jira & Confluence) and passes them to the LLM

Why Use Vercel AI SDK with the Atlassian (Jira & Confluence) MCP Server

Vercel AI SDK provides unique advantages when paired with Atlassian (Jira & Confluence) through the Model Context Protocol.

01

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

02

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime — same Atlassian (Jira & Confluence) integration everywhere

03

Built-in streaming UI primitives let you display Atlassian (Jira & Confluence) tool results progressively in React, Svelte, or Vue components

04

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

Atlassian (Jira & Confluence) + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the Atlassian (Jira & Confluence) MCP Server delivers measurable value.

01

AI-powered web apps: build dashboards that query Atlassian (Jira & Confluence) in real-time and stream results to the UI with zero loading states

02

API backends: create serverless endpoints that orchestrate Atlassian (Jira & Confluence) tools and return structured JSON responses to any frontend

03

Chatbots with tool use: embed Atlassian (Jira & Confluence) capabilities into conversational interfaces with streaming responses and tool call visibility

04

Internal tools: build admin panels where team members interact with Atlassian (Jira & Confluence) through natural language queries

Atlassian (Jira & Confluence) MCP Tools for Vercel AI SDK (9)

These 9 tools become available when you connect Atlassian (Jira & Confluence) to Vercel AI SDK via MCP:

01

get_issue

Get Jira issue details by exact key

02

get_myself

Get current authenticated user information

03

get_page

Get Confluence page rich text content

04

list_boards

Often used before retrieving backlogs or active sprints. List all Jira agile boards

05

list_projects

Useful for discovering project keys needed for querying specific domains or boards. List all Jira projects

06

list_spaces

List all Confluence spaces

07

list_sprints

List sprints for a specific Jira board

08

search_content

Search Confluence content with CQL

09

search_issues

Search Jira issues with JQL

Example Prompts for Atlassian (Jira & Confluence) in Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Atlassian (Jira & Confluence) immediately.

01

"Get my active Jira sprint tickets related to frontend errors."

02

"Find Confluence wiki pages detailing the 'Payment Gateway API' architecture."

03

"List all active boards and the sprints currently running in them."

Troubleshooting Atlassian (Jira & Confluence) MCP Server with Vercel AI SDK

Common issues when connecting Atlassian (Jira & Confluence) to Vercel AI SDK through the Vinkius, and how to resolve them.

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

Atlassian (Jira & Confluence) + Vercel AI SDK FAQ

Common questions about integrating Atlassian (Jira & Confluence) MCP Server with Vercel AI SDK.

01

How does the Vercel AI SDK connect to MCP servers?

Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
02

Can I use MCP tools in Edge Functions?

Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
03

Does it support streaming tool results?

Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.

Connect Atlassian (Jira & Confluence) to Vercel AI SDK

Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.