klauseduard vibe coded jira mcp

klauseduard vibe coded jira mcp avatar

by klauseduard

What is klauseduard vibe coded jira mcp

JIRA MCP Server

A simple Model Context Protocol (MCP) "vibe-coded" server for integrating JIRA with Cursor IDE. MCP is an open protocol that enables seamless integration between LLM applications and external data sources and tools.

This implementation started out by discarding another JIRA MCP server that we failed to init in Cursor.

BEWARE! Even this document is almost entirely written by AI coding assistant.

Features

  • Get JIRA issues by key
  • Search issues using JQL (JIRA Query Language)
  • Create and update issues (note: may have limitations with heavily customized JIRA projects)
  • Add comments to issues
  • Clone issues (useful for working around mandatory custom fields, but may have limitations with complex project configurations)
  • Configurable field selection
  • Pagination support
  • Detailed error handling and logging
  • Log work

User Workflows

Search and Filter Flow

graph LR
    A[Start Search] -->|Enter JQL| B[Search Query]
    B -->|Apply Filters| C[Results]
    C -->|Select Fields| D[Customized View]
    D -->|Pagination| E[More Results]
    
    subgraph Search Options
        F[JQL Query]
        G[Field Selection]
        H[Result Limit]
        I[Start Position]
    end
    
    B -->|Uses| F
    C -->|Uses| G
    C -->|Uses| H
    C -->|Uses| I

Issue Cloning Flow

graph LR
    A[Find Source Issue] -->|Copy Key| B[Clone Issue]
    B -->|Customize Fields| C[Modified Clone]
    C -->|Create| D[New Issue]
    
    subgraph Clone Options
        E[Change Project]
        F[Modify Fields]
        G[Copy Attachments]
        H[Add Source Link]
    end
    
    B -->|Can Use| E
    B -->|Can Use| F
    B -->|Can Use| G
    B -->|Can Use| H

For detailed technical architecture and system workflows, including issue lifecycle and authentication flows, see ARCHITECTURE.md.

About MCP

This server implements the Model Context Protocol specification, allowing Cursor IDE to seamlessly interact with JIRA data through its AI features. The protocol standardizes how LLM applications communicate with external data sources and tools.

Setup

  1. Create a virtual environment:
python -m venv venv
source venv`/bin/activate`  # On Windows: venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt
  1. Configure environment variables: Create a .env file with:
JIRA_URL=your_jira_url
JIRA_USERNAME=your_username
JIRA_API_TOKEN=your_api_token

Usage

Run the server:

./run-jira-mcp.sh

Development

The project follows a modular structure:

src/
โ”œโ”€โ”€ core/           # Core JIRA client implementation
โ”‚   โ”œโ”€โ”€ __init__.py
โ”‚   โ”œโ”€โ”€ client.py   # JiraClient class
โ”‚   โ””โ”€โ”€ config.py   # Configuration management
โ”œโ”€โ”€ models/         # Pydantic models for validation
โ”‚   โ”œโ”€โ”€ __init__.py
โ”‚   โ”œโ”€โ”€ comment.py  # Comment-related models
โ”‚   โ”œโ”€โ”€ issue.py    # Issue-related models
โ”‚   โ””โ”€โ”€ worklog.py  # Worklog-related models
โ””โ”€โ”€ operations/     # MCP operation implementations
    โ”œโ”€โ”€ __init__.py
    โ”œโ”€โ”€ comments.py # Comment operations
    โ”œโ”€โ”€ issues.py   # Issue operations
    โ”œโ”€โ”€ projects.py # Project operations
    โ””โ”€โ”€ worklog.py  # Worklog operations

Key Components

  1. Models (src/models/)

    • IssueType, IssueArgs - Issue creation/update models
    • IssueTransitionArgs - Issue state transition model
    • CloneIssueArgs - Issue cloning model
    • CommentArgs, GetCommentsArgs - Comment models
    • LogWorkArgs - Work logging model
  2. Core (src/core/)

    • JiraClient - Main JIRA API client
    • JiraConfig - Configuration management
    • Error handling and logging
  3. Operations (src/operations/)

    • Issue management (get, search, create, update, clone)
    • Comment handling (add, get)
    • Work logging
    • Project listing

The project follows the implementation plan outlined in IMPLEMENTATION_PLAN.md.

Current version: v0.4

  • โœ… Basic JIRA integration
  • โœ… Search functionality with JQL support
  • โœ… Issue management (create, update, clone) with limitations for heavily customized projects
  • โœ… Comment functionality
  • โœ… Work logging

Related Links

  • Model Context Protocol - The main MCP project
  • MCP Python SDK - The SDK we use to implement this server
  • MCP Documentation - Protocol documentation and specifications

License

MIT

Security Considerations

This tool is primarily designed for personal workflow automation and individual developer use. Please be aware of the following security considerations:

โš ๏ธ Usage Recommendations

  • Personal/Development Use: Ideal for individual developers managing their JIRA workflows
  • Small Team Use: Suitable for trusted team environments with proper security measures
  • NOT Recommended For:
    • Production deployment in its current form
    • Multi-tenant environments
    • Public-facing services
    • Processing sensitive/regulated data

๐Ÿ”’ Security Requirements

If you choose to use this tool, please ensure:

  1. Your JIRA instance uses HTTPS
  2. You're using API tokens (not passwords) for authentication
  3. Your .env file is properly secured and not committed to version control
  4. You understand the risks of running third-party tools with JIRA access

๐Ÿ›ก๏ธ Best Practices

  1. Regularly rotate your API tokens
  2. Monitor your JIRA audit logs for unexpected activity
  3. Use the most recent version of the tool
  4. Review the code before use in your environment

๐Ÿ“ Note on Enterprise Usage

This tool is not currently hardened for enterprise security requirements. If you need a solution for enterprise deployment, consider:

  • Implementing additional security controls
  • Conducting a security review
  • Contributing security improvements back to the project
  • Using official enterprise-grade alternatives

For security-related concerns or to report vulnerabilities, please open an issue or contact the maintainers directly.

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Frequently Asked Questions

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.

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