jira-tools-mcp 0.2.2
Jira MCP for controlling Jira through Jira Command Line.
Requires Python: >=3.12

![Jira MCP](/docs/images/jiramcp.png)

# Jira MCP - The most feature-rich MCP server for Jira

![Claude Demo](/docs/images/claude.gif)

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[![ruff](https://img.shields.io/badge/ruff-d7ff64.svg?style=for-the-badge&logo=ruff&logoColor=black)](https://docs.astral.sh/ruff/)
[![uv](https://img.shields.io/badge/uv-000000.svg?style=for-the-badge&logo=uv&logoColor=white)](https://docs.astral.sh/uv/)
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<!-- mcp-name: io.github.xcollantes/jira-mcp -->

**The most powerful and feature-rich MCP server for Jira integration.** Control Jira through AI-powered LLM clients like Cursor, Claude Desktop, Windsurf, and ChatGPT using the Model Context Protocol.

## Why Jira MCP is the Best Choice

- **Enterprise Ready**: Runs completely locally with no third-party data sharing. Safe for corporate environments.
- **Full-Featured**: Complete Jira control including create, update, search, transition, and manage tickets using natural language.
- **Easy Setup**: Pre-built binaries for Linux, macOS, and Windows. Get started in minutes.
- **Actively Maintained**: Open source, MIT licensed, with regular updates and community support.
- **AI-Native**: Built specifically for the Model Context Protocol to provide the best AI-to-Jira experience.

## Getting started

**[Jira MCP Server](https://jira.xaviercollantes.dev)**

## Installation

### Install jira-cli

The MCP server uses the `jira-cli` to execute Jira commands.

Follow the installation instructions for your operating system:
<https://github.com/ankitpokhrel/jira-cli?tab=readme-ov-file#installation>

### Get Jira API Token

Depending on your implementation of Jira (Cloud or Self-Hosted), you will need
to use a different authentication type.

Get your API token from: <https://id.atlassian.com/manage-profile/security/api-tokens>

You will need to set the following environment variables:

- `JIRA_API_TOKEN` - Your Jira API token
- `JIRA_AUTH_TYPE` - Authentication type (`bearer` for token, `basic` for Jira
  account API token, `password` for Jira account password)

**Recommended:** Pass these variables in your MCP client configuration using the
`env` field (shown in the configuration examples below). This is more reliable
than shell environment variables because GUI applications like Cursor and
Windsurf do not inherit variables from `.bashrc` or `.zshrc`.

Other ways to add credentials to your environment:
<https://github.com/ankitpokhrel/jira-cli/discussions/356>

### Start Jira CLI

```bash
jira init
```

This should initialize the Jira CLI by asking for your Jira URL and credentials.

### Test Jira CLI

```bash
jira issue list
```

This should return a list of issues in Jira.

### MCP Server: Option 1: Download binaries (Recommended)

Download the latest release for your operating system from the [Releases
page](https://github.com/xcollantes/jira-mcp/releases).

| Operating System | Binary |
|------------------|--------|
| Linux | `jira-mcp-linux` |
| Windows | `jira-mcp-windows.exe` |
| macOS (Apple Silicon) | `jira-mcp-macos-apple-silicon-arm64` |
| macOS (Intel) | `jira-mcp-macos-x64` |

#### Linux

```bash
# Download the binary
curl -L -o jira-mcp https://github.com/xcollantes/jira-mcp/releases/latest/download/jira-mcp-linux

# Make it executable
chmod +x jira-mcp

# Move to a directory in your PATH (optional)
sudo mv jira-mcp /usr/local/bin/
```

Add to your LLM client configuration:

**NOTE:** Make sure to replace `/usr/local/bin/jira-mcp` with the path to the
binary on your machine if you moved it to a different location.

```json
{
  "mcpServers": {
    "jira": {
      "command": "/usr/local/bin/jira-mcp",
      "env": {
        "JIRA_API_TOKEN": "your-api-token",
        "JIRA_AUTH_TYPE": "basic"
      }
    }
  }
}
```

#### macOS

```bash
# For Apple Silicon (M1/M2/M3)
curl -L -o jira-mcp https://github.com/xcollantes/jira-mcp/releases/latest/download/jira-mcp-macos-apple-silicon-arm64

# For Intel Macs
curl -L -o jira-mcp https://github.com/xcollantes/jira-mcp/releases/latest/download/jira-mcp-macos-x64

# Make it executable
chmod +x jira-mcp

# Move to a directory in your PATH (optional)
sudo mv jira-mcp /usr/local/bin/
```

**Note:** macOS may block the binary on first run. If you see a security
warning, go to **System Settings > Privacy & Security** and click **Allow
Anyway**, or run:

```bash
xattr -d com.apple.quarantine /usr/local/bin/jira-mcp
```

Add to your LLM client configuration:

**NOTE:** Make sure to replace `/usr/local/bin/jira-mcp` with the path to the
binary on your machine if you moved it to a different location.

```json
{
  "mcpServers": {
    "jira": {
      "command": "/usr/local/bin/jira-mcp",
      "env": {
        "JIRA_API_TOKEN": "your-api-token",
        "JIRA_AUTH_TYPE": "basic"
      }
    }
  }
}
```

#### Windows

1. Download `jira-mcp-windows.exe` from the [Releases
   page](https://github.com/xcollantes/jira-mcp/releases).
2. Move the executable to a convenient location (e.g., `C:\Program
   Files\jira-mcp\`).

Add to your LLM client configuration:

```json
{
  "mcpServers": {
    "jira": {
      "command": "C:\\Program Files\\jira-mcp\\jira-mcp-windows.exe",
      "env": {
        "JIRA_API_TOKEN": "your-api-token",
        "JIRA_AUTH_TYPE": "basic"
      }
    }
  }
}
```

**NOTE:** Make sure to replace `C:\\Program
Files\\jira-mcp\\jira-mcp-windows.exe` with the path to the binary on your
machine if you moved it to a different location.

### MCP Server: Option 2: Development setup with uv

Get repo:

```bash
git clone https://github.com/xcollantes/jira-mcp.git
cd jira-mcp
```

Add MCP server to your choice of LLM client:

**NOTE:** You will need to look up for your specific client on how to add MCPs.

Usually the JSON file for the LLM client will look like this:

```json
{
  "mcpServers": {
    "jira": {
      "command": "uv",
      "args": [
        "--directory",
        "/ABSOLUTE/PATH/TO/REPO/ROOT",
        "run",
        "python",
        "-m",
        "src.main"
      ],
      "env": {
        "JIRA_API_TOKEN": "your-api-token",
        "JIRA_AUTH_TYPE": "basic"
      }
    }
  }
}
```

This will tell your LLM client application that there's a tool that can be
called by calling `uv --directory /ABSOLUTE/PATH/TO/REPO run python -m
src.main`.

Install UV: <https://docs.astral.sh/uv/getting-started/installation/>

### MCP Server: Option 3: Install globally with pipx

```bash
# Install pipx if you haven't already
brew install pipx
pipx ensurepath

# Clone and install the MCP server
git clone https://github.com/xcollantes/jira-mcp.git
cd jira-mcp
pipx install -e .
```

## How it works

1. You enter some questions or prompt to a LLM Client such as the Claude
   Desktop, Cursor, Windsurf, or ChatGPT.
2. The client sends your question to the LLM model (Sonnet, Grok, ChatGPT)
3. LLM analyzes the available tools and decides which one(s) to use
   - The LLM you're using will have a context of the tools and what each tool is
     meant for in human language.
   - Alternatively without MCPs, you could include in the prompt the endpoints
     and a description on each endpoint for the LLM to "call on". Then you could
     copy and paste the text commands into the terminal on your machine.
   - MCPs provide a more deterministic and standardized method on LLM-to-server
     interactions.
4. The client executes the chosen tool(s) through the MCP server.
   - The MCP server is either running local on your machine or an endpoint
     hosting the MCP server remotely.
5. The results are sent back to LLM.
6. LLM formulates a natural language response and one or both of the following
   happen:
   - The response is displayed to you with data from the MCP server
   - Some action is performed using the MCP server

## Development

### Logging

Do not use `print` statements for logging. Use the logging module instead.
Writing to stdout will corrupt the JSON-RPC messages and break your server.

### Pre-commit

This project uses [pre-commit](https://pre-commit.com/) to run
[ruff](https://docs.astral.sh/ruff/) linting and formatting checks, and
[pytest](https://docs.pytest.org/) tests before each commit.

To set up pre-commit hooks:

```bash
uv sync
uv run pre-commit install
```

Once installed, ruff and pytest will automatically run when you commit. To run
checks manually on all files:

```bash
uv run pre-commit run --all-files
```

## Docstrings / Tool decorator parameters

MCP.tools decorator parameters are especially important as this is the human
readable text that the LLM has context of. This will be treated as part of the
prompt when fed to the LLM and this will decide when to use each tool.

## Architecture

MCP follows a client-server architecture where an **MCP host** (an AI
application like Cursor or ChatGPT desktop) establishes connections to one or
more **MCP servers**. The **MCP host** accomplishes this by creating one **MCP
client** for each **MCP server**. Each MCP client maintains a dedicated
connection with its corresponding MCP server.

<https://modelcontextprotocol.io/docs/learn/architecture>

## Pitfalls / Troubleshooting

## Edit the jira-cli config file

On MacOS:

```text
/Users/<your-username>/.config/.jira/.config.yml
```

## 404 error when using `jira init`

If you get a 404 error when using `jira init`, you may need to edit the jira-cli
config file to point to the correct Jira instance. There are only 3 possible
values for the auth type so try each one. `basic`, `password`, or `bearer`.