Backlog MCP Server

Backlog MCP Server

📘 日本語でのご利用ガイド

A Model Context Protocol (MCP) server for interacting with the Backlog API. This server provides tools for managing projects, issues, wiki pages, and more in Backlog through AI agents like Claude Desktop / Cline / Cursor etc.

Features

• Project tools (create, read, update, delete)
• Issue tracking and comments (create, update, delete, list)
• Version/Milestone management (create, read, update, delete)
• Wiki page support
• Git repository and pull request tools
• Notification tools
• GraphQL-style field selection for optimized responses
• Token limiting for large responses

Getting Started

Requirements

• Docker
• A Backlog account with API access
• API key from your Backlog account

Option 1: Install via Docker

The easiest way to use this MCP server is through MCP configurations:

1. Open MCP settings
2. Navigate to the MCP configuration section
3. Add the following configuration:

Replace your-domain.backlog.com with your Backlog domain and your-api-key with your Backlog API key.

✅ If you cannot use --pull always, you can manually update the image using:

Option 2: Install via npx

You can also run the server directly using npx without cloning the repository. This is a convenient way to run the server without a full installation.

1. Open MCP settings
2. Navigate to the MCP configuration section
3. Add the following configuration:

Replace your-domain.backlog.com with your Backlog domain and your-api-key with your Backlog API key.

Option 3: Manual Setup (Node.js)

1. Clone and install:
   git clone https://github.com/nulab/backlog-mcp-server.git cd backlog-mcp-server npm install npm run build
2. Set your json to use as MCP

Tool Configuration

You can selectively enable or disable specific toolsets using the --enable-toolsets command-line flag or the ENABLE_TOOLSETS environment variable. This allows better control over which tools are available to the AI agent and helps reduce context size.

Available Toolsets

The following toolsets are available (enabled by default when "all" is used):

Specifying Toolsets

You can control toolset activation in the following ways:

Using via CLI:

Or via environment variable:

If all is specified, all available toolsets will be enabled. This is also the default behavior.

Using selective toolsets can be helpful if the toolset list is too large for your AI agent or if certain tools are causing performance issues. In such cases, disabling unused toolsets may improve stability.

🧩 Tip: project toolset is highly recommended, as many other tools rely on project data as an entry point.

Dynamic Toolset Discovery (Experimental)

If you're using the MCP server with AI agents, you can enable dynamic discovery of toolsets at runtime:

Enabling via CLI:

Or via environment variable::

With dynamic toolsets enabled, the LLM will be able to list and activate toolsets on demand via tool interface.

Available Tools

Toolset: space

Tools for managing Backlog space settings and general information.

• get_space: Returns information about the Backlog space.
• get_users: Returns list of users in the Backlog space.
• get_myself: Returns information about the authenticated user.

Toolset: project

Tools for managing projects, categories, custom fields, and issue types.

• get_project_list: Returns list of projects.
• add_project: Creates a new project.
• get_project: Returns information about a specific project.
• update_project: Updates an existing project.
• delete_project: Deletes a project.

Toolset: issue

Tools for managing issues, their comments, and related items like priorities, categories, custom fields, issue types, resolutions, and watching lists.

• get_issue: Returns information about a specific issue.
• get_issues: Returns list of issues.
• count_issues: Returns count of issues.
• add_issue: Creates a new issue in the specified project.
• update_issue: Updates an existing issue.
• delete_issue: Deletes an issue.
• get_issue_comments: Returns list of comments for an issue.
• add_issue_comment: Adds a comment to an issue.
• get_priorities: Returns list of priorities.
• get_categories: Returns list of categories for a project.
• get_custom_fields: Returns list of custom fields for a project.
• get_issue_types: Returns list of issue types for a project.
• get_resolutions: Returns list of issue resolutions.
• get_watching_list_items: Returns list of watching items for a user.
• get_watching_list_count: Returns count of watching items for a user.
• get_version_milestone_list: Returns list of version milestones for a project.
• add_version_milestone: Creates a new version milestone for a project.
• update_version_milestone: Updates an existing version milestone.
• delete_version_milestone: Deletes a version milestone.

Toolset: wiki

Tools for managing wiki pages.

• get_wiki_pages: Returns list of Wiki pages.
• get_wikis_count: Returns count of wiki pages in a project.
• get_wiki: Returns information about a specific wiki page.
• add_wiki: Creates a new wiki page.

Toolset: git

Tools for managing Git repositories and pull requests.

• get_git_repositories: Returns list of Git repositories for a project.
• get_git_repository: Returns information about a specific Git repository.
• get_pull_requests: Returns list of pull requests for a repository.
• get_pull_requests_count: Returns count of pull requests for a repository.
• get_pull_request: Returns information about a specific pull request.
• add_pull_request: Creates a new pull request.
• update_pull_request: Updates an existing pull request.
• get_pull_request_comments: Returns list of comments for a pull request.
• add_pull_request_comment: Adds a comment to a pull request.
• update_pull_request_comment: Updates a comment on a pull request.

Toolset: notifications

Tools for managing user notifications.

• get_notifications: Returns list of notifications.
• get_notifications_count: Returns count of notifications.
• reset_unread_notification_count: Resets unread notification count.
• mark_notification_as_read: Marks a notification as read.

Toolset: document

Tools for managing documents and document trees in Backlog projects.

• get_document_tree: Returns the hierarchical tree of documents for a project, including folders and ne
• get_documents: Returns a flat list of documents in a project or folder.
• get_document: Returns detailed information about a specific document, including metadata, content, an

Usage Examples

Once the MCP server is configured in AI agents, you can use the tools directly in your conversations. Here are some examples:

• Listing Projects

• Creating a New Issue

• Getting Project Details

• Working with Git Repositories

• Managing Pull Requests

• Watching Items

i18n / Overriding Descriptions

You can override the descriptions of tools by creating a .backlog-mcp-serverrc.json file in your home directory.

The file should contain a JSON object with the tool names as keys and the new descriptions as values.
For example:

When the server starts, it determines the final description for each tool based on the following priority:

1. Environment variables (e.g., BACKLOG_MCP_TOOL_ADD_ISSUE_COMMENT_DESCRIPTION)
2. Entries in .backlog-mcp-serverrc.json - Supported configuration file formats: .json, .yaml, .yml
3. Built-in fallback values (English)

Sample config:

Exporting Current Translations

You can export the current default translations (including any overrides) by running the binary with the --export-translations flag.

This will print all tool descriptions to stdout, including any customizations you have made.

Example:

or

Using a Japanese Translation Template

A sample Japanese configuration file is provided at:

To use it, copy it to your home directory as .backlog-mcp-serverrc.json:

You can then edit the file to customize the descriptions as needed.

Using Environment Variables

Alternatively, you can override tool descriptions via environment variables.

The environment variable names are based on the tool keys, prefixed with BACKLOG_MCP_ and written in uppercase.

Example: To override the TOOL_ADD_ISSUE_COMMENT_DESCRIPTION:

The server loads the config file synchronously at startup.

Environment variables always take precedence over the config file.

Advanced Features

Tool Name Prefixing

Add prefix to tool names with:

or via environment variable:

This is especially useful if you're using multiple MCP servers or tools in the same environment and want to avoid name collisions. For example, get_project can become backlog_get_project to distinguish it from similarly named tools provided by other services.

Response Optimization & Token Limits

Field Selection (GraphQL-style)

Or environment variable:

Then, request only specific fields:

The AI will use field selection to optimize the response:

Benefits:

• Reduce response size by requesting only needed fields
• Focus on specific data points
• Improve performance for large responses

Token Limiting

Large responses are automatically limited to prevent exceeding token limits:

• Default limit: 50,000 tokens
• Configurable via MAX_TOKENS environment variable
• Responses exceeding the limit are truncated with a message

You can change this using:

If a response exceeds the limit, it will be truncated with a warning.

Note: This is a best-effort mitigation, not a guaranteed enforcement.

Full Custom Configuration Example

This section demonstrates advanced configuration using multiple environment variables. These are experimental features and may not be supported across all MCP clients. This is not part of the MCP standard specification and should be used with caution.

Development

Running Tests

Adding New Tools

1. Create a new file in src/tools/ following the pattern of existing tools
2. Create a corresponding test file
3. Add the new tool to src/tools/tools.ts
4. Build and test your changes

Command Line Options

The server supports several command line options:

• --export-translations: Export all translation keys and values
• --optimize-response: Enable GraphQL-style field selection
• --max-tokens=NUMBER: Set maximum token limit for responses
• --prefix=STRING: Optional string prefix to prepend to all tool names (default: "")
• --enable-toolsets <toolsets...>: Specify which toolsets to enable (comma-separated or multiple arguments). Defaults to "all". Example: --enable-toolsets space,project or --enable-toolsets issue --enable-toolsets git Available toolsets: space, project, issue, wiki, git, notifications.

Example:

License

This project is licensed under the MIT License.

Please note: This tool is provided under the MIT License without any warranty or official support.
Use it at your own risk after reviewing the contents and determining its suitability for your needs.
If you encounter any issues, please report them via GitHub Issues.