Jira & Confluence MCP Server

Instructions

Implementation Reference

• src/jira_server.py:261-286 (handler)

  The core handler function for the 'jira_get_issue' tool. It fetches the Jira issue by key using the Atlassian client, extracts relevant fields, structures them into a JiraIssue model, and returns the JSON-serialized details.

  async def _get_issue(self, arguments: dict) -> List[TextContent]:
      """Get details of a specific issue"""
      issue_key = arguments["issue_key"]
      
      issue = self.jira_client.issue(issue_key)
      fields = issue.get("fields", {})
      
      issue_details = JiraIssue(
          key=issue["key"],
          summary=fields.get("summary", ""),
          description=fields.get("description", ""),
          status=fields.get("status", {}).get("name", ""),
          assignee=fields.get("assignee", {}).get("displayName", "") if fields.get("assignee") else None,
          reporter=fields.get("reporter", {}).get("displayName", ""),
          created=fields.get("created", ""),
          updated=fields.get("updated", ""),
          priority=fields.get("priority", {}).get("name", "") if fields.get("priority") else None,
          issue_type=fields.get("issuetype", {}).get("name", ""),
          project=fields.get("project", {}).get("key", "")
      )
      
      return [TextContent(
          type="text",
          text=issue_details.model_dump_json(indent=2)
      )]

• src/jira_server.py:71-84 (registration)

  Tool registration in the list_tools() method, defining the name, description, and input schema for 'jira_get_issue'.

  Tool(
      name="jira_get_issue",
      description="Get details of a specific Jira issue",
      inputSchema={
          "type": "object",
          "properties": {
              "issue_key": {
                  "type": "string",
                  "description": "Issue key (e.g., PROJ-123)"
              }
          },
          "required": ["issue_key"]
      }
  ),

• src/jira_server.py:27-40 (schema)

  Pydantic BaseModel schema used to structure and validate the output data for the jira_get_issue tool.

  class JiraIssue(BaseModel):
      """Jira issue model"""
      key: str
      summary: str
      description: Optional[str] = None
      status: str
      assignee: Optional[str] = None
      reporter: str
      created: str
      updated: str
      priority: Optional[str] = None
      issue_type: str
      project: str

• src/jira_server.py:199-200 (registration)

  Dispatch logic in the call_tool() handler that routes calls to 'jira_get_issue' to the _get_issue implementation.

  elif name == "jira_get_issue":
      return await self._get_issue(arguments)