​
No-Code

Connect to enterprise-grade MCP servers instantly!

Get Started →

​
For Developer

Follow the instructions below to integrate Jira MCP server to your AI application using our API or SDK.

​
Prerequisites

​
1. Create a Jira MCP Server

Use the following endpoint to create a new remote Jira MCP server instance:

​
Request

from klavis import Klavis
from klavis.types import McpServerName, ConnectionType

klavis_client = Klavis(api_key="<YOUR_API_KEY>")

# Create a Jira MCP server instance
jira_server = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.JIRA,
    user_id="<YOUR_USER_ID>",
    platform_name="<YOUR_PLATFORM_NAME>",
)

​
Response

{
  "serverUrl": "https://jira-mcp-server.klavis.ai/mcp/?instance_id=<instance-id>",
  "instanceId": "<instance-id>",
  "oauthUrl": "https://api.klavis.ai/oauth/jira/authorize?instance_id=<instance-id>"
}
serverUrl specifies the endpoint of the Jira MCP server, which allows you to interact with Jira projects and issues.
instanceId is used to get an authentication token. After you complete the OAuth flow, this token allows the MCP server to access Jira on your behalf.

​
2. Jira OAuth Flow

Redirect users to the OAuth authorization flow:

import webbrowser

webbrowser.open(jira_server.oauth_url)

​
Watch the Example

​
Explore MCP Server Tools