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

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.
• add_watching: Adds a new watch to an issue.
• update_watching: Updates an existing watch note.
• delete_watching: Deletes a watch from an issue.
• mark_watching_as_read: Marks a watch as read.
• 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

Advanced Features

Tool Name Prefixing

Add prefix to tool names with:

--prefix backlog_

or via environment variable:

PREFIX="backlog_"

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)

--optimize-response

Or environment variable:

OPTIMIZE_RESPONSE=1

Then, request only specific fields:

get_project(projectIdOrKey: "PROJECT-KEY", fields: "{ name key description }")

The AI will use field selection to optimize the response:

get_project(projectIdOrKey: "PROJECT-KEY", fields: "{ name key description }")

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:

MAX_TOKENS=10000

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.

{
  "mcpServers": {
    "backlog": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "BACKLOG_DOMAIN",
        "-e",
        "BACKLOG_API_KEY",
        "-e",
        "MAX_TOKENS",
        "-e",
        "OPTIMIZE_RESPONSE",
        "-e",
        "PREFIX",
        "-e",
        "ENABLE_TOOLSETS",
        "ghcr.io/nulab/backlog-mcp-server"
      ],
      "env": {
        "BACKLOG_DOMAIN": "your-domain.backlog.com",
        "BACKLOG_API_KEY": "your-api-key",
        "MAX_TOKENS": "10000",
        "OPTIMIZE_RESPONSE": "1",
        "PREFIX": "backlog_",
        "ENABLE_TOOLSETS": "space,project,issue",
        "ENABLE_DYNAMIC_TOOLSETS": "1"
      }
    }
  }
}

Development

Running Tests

pnpm test

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:

• --transport stdio|http: MCP transport (default: stdio). Use http for Streamable HTTP.
• --http-host, --http-port, --http-path: HTTP bind address, port, and path (defaults: 127.0.0.1, 3333, /mcp).
• --http-json-response: Prefer JSON responses over SSE when the transport supports it.
• --http-allowed-hosts: Comma-separated allowed Host headers when binding to all interfaces.
• --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:

node build/index.js --optimize-response --max-tokens=100000 --prefix="backlog_" --enable-toolsets space,issue

HTTP example:

node build/index.js --transport http --http-port 3333 --http-path /mcp

Multi-Organization Support

This server can be configured to access multiple Backlog organizations from a single MCP server instance.

Configuration

Configure one env pair per organization and set a default organization:

BACKLOG_DEFAULT_ORG=COMPANY_A
BACKLOG_ORG_COMPANY_A_DOMAIN=company-a.backlog.com
BACKLOG_ORG_COMPANY_A_API_KEY=your-company-a-api-key
BACKLOG_ORG_COMPANY_B_DOMAIN=company-b.backlog.com
BACKLOG_ORG_COMPANY_B_API_KEY=your-company-b-api-key

This works whether the variables come from a local .env, your shell environment, or an MCP client config env block.

Example MCP config:

{
  "env": {
    "BACKLOG_DEFAULT_ORG": "COMPANY_A",
    "BACKLOG_ORG_COMPANY_A_DOMAIN": "company-a.backlog.com",
    "BACKLOG_ORG_COMPANY_A_API_KEY": "your-company-a-api-key",
    "BACKLOG_ORG_COMPANY_B_DOMAIN": "company-b.backlog.com",
    "BACKLOG_ORG_COMPANY_B_API_KEY": "your-company-b-api-key"
  }
}

If no multi-organization env vars are set, the server falls back to the existing single-organization configuration:

BACKLOG_DOMAIN=your-domain.backlog.com
BACKLOG_API_KEY=your-api-key

Tool Usage

All normal tools accept an optional organization input field. When provided, the tool call is routed to that Backlog organization.

Examples:

{
  "organization": "COMPANY_B",
  "projectKey": "PROJECT"
}

If organization is omitted:

• the organization named by BACKLOG_DEFAULT_ORG is used
• if multi-organization env vars are present and BACKLOG_DEFAULT_ORG is missing, the server fails at startup

Organization Discovery

The server provides a list_organizations tool that returns the configured organization names, their domains, and which one is the default.

Example response:

[
  {
    "name": "COMPANY_A",
    "domain": "company-a.backlog.com",
    "isDefault": true
  },
  {
    "name": "COMPANY_B",
    "domain": "company-b.backlog.com",
    "isDefault": false
  }
]

Notes

• For multi-org mode, every organization must define both BACKLOG_ORG_<NAME>_DOMAIN and BACKLOG_ORG_<NAME>_API_KEY.
• The <NAME> part is the organization name exposed through the organization tool input and list_organizations.

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.

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:

{
  "mcpServers": {
    "backlog": {
      "command": "docker",
      "args": [
        "run",
        "--pull",
        "always",
        "-i",
        "--rm",
        "-e",
        "BACKLOG_DOMAIN",
        "-e",
        "BACKLOG_API_KEY",
        "ghcr.io/nulab/backlog-mcp-server"
      ],
      "env": {
        "BACKLOG_DOMAIN": "your-domain.backlog.com",
        "BACKLOG_API_KEY": "your-api-key"
      }
    }
  }
}

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:

docker pull ghcr.io/nulab/backlog-mcp-server:latest

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:

{
  "mcpServers": {
    "backlog": {
      "command": "npx",
      "args": ["backlog-mcp-server"],
      "env": {
        "BACKLOG_DOMAIN": "your-domain.backlog.com",
        "BACKLOG_API_KEY": "your-api-key"
      }
    }
  }
}

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:

   Copy & paste — that's itCopy

   git clone https://github.com/nulab/backlog-mcp-server.git
   cd backlog-mcp-server
   pnpm install
   pnpm run build

2. Create .env from template and set required variables:

cp .env.example .env

Set the following values in .env:

• BACKLOG_DOMAIN=your-domain.backlog.com
• BACKLOG_API_KEY=your-api-key

3. Run locally:

pnpm run dev

4. Set your json to use as MCP

{
  "mcpServers": {
    "backlog": {
      "command": "node",
      "args": ["your-repository-location/build/index.js"],
      "env": {
        "BACKLOG_DOMAIN": "your-domain.backlog.com",
        "BACKLOG_API_KEY": "your-api-key"
      }
    }
  }
}

HTTP transport (Streamable HTTP)

By default the server uses stdio. To run the MCP Streamable HTTP transport instead (JSON-RPC over HTTP, same tools as stdio), start with --transport http or set MCP_TRANSPORT=http.

pnpm run build
MCP_TRANSPORT=http MCP_HTTP_PORT=3333 node build/index.js

• Endpoint: POST, GET, and DELETE on http://<host>:<port><path> (default path /mcp).
• Session: After initialize, clients must send the mcp-session-id header on later requests (as returned by the server).
• Security: Default bind is 127.0.0.1. Do not expose the HTTP port to untrusted networks without authentication and TLS; it allows full use of your Backlog API key via MCP tools.

Environment variables (CLI flags override when both are set):

OAuth 2.0 Authentication (Remote MCP)

When exposing the MCP server over a network, you can enable OAuth 2.0 authentication so that each user authenticates with their own Backlog account instead of sharing a single API key.

The server implements the MCP Third-Party Authorization Flow by acting as both an OAuth authorization server (for MCP clients) and an OAuth client (for Backlog).

Prerequisites

1. Register an OAuth application in your Backlog space:

   • Go to your Backlog space → Personal Settings → Register Application
   • Set the Redirect URI to <MCP_SERVER_BASE_URL>/callback (e.g., https://mcp.example.com/callback)
   • Note the Client ID and Client Secret

2. Set the following environment variables (in addition to BACKLOG_DOMAIN):

Note: BACKLOG_API_KEY is not required when OAuth is enabled — each user authenticates with their own Backlog account.

Example

BACKLOG_DOMAIN=your-space.backlog.com \
BACKLOG_OAUTH_CLIENT_ID=your-client-id \
BACKLOG_OAUTH_CLIENT_SECRET=your-client-secret \
MCP_SERVER_BASE_URL=https://mcp.example.com \
node build/index.js --transport http --http-host 0.0.0.0 --http-port 3333

The server automatically exposes the following OAuth endpoints when OAuth is enabled:

MCP clients that support the MCP authorization specification will use these endpoints automatically.

Limitations:

• OAuth mode currently supports a single Backlog organization. It is not compatible with the multi-organization configuration.
• Client registrations and tokens are stored in memory and will be lost on server restart.

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:

--enable-toolsets space,project,issue

Or via environment variable:

ENABLE_TOOLSETS="space,project,issue"

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:

--dynamic-toolsets

Or via environment variable::

-e DYNAMIC_TOOLSETS=1 \

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

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

Could you list all my Backlog projects?

• Creating a New Issue

Create a new bug issue in the PROJECT-KEY project with high priority titled "Fix login page error"

• Getting Project Details

Show me the details of the PROJECT-KEY project

• Working with Git Repositories

List all Git repositories in the PROJECT-KEY project

• Managing Pull Requests

Show me all open pull requests in the repository "repo-name" of PROJECT-KEY project

Create a new pull request from branch "feature/new-feature" to "main" in the repository "repo-name" of PROJECT-KEY project

• Watching Items

Show me all items I'm watching

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:

{
  "TOOL_ADD_ISSUE_COMMENT_DESCRIPTION": "An alternative description",
  "TOOL_CREATE_PROJECT_DESCRIPTION": "Create a new project in Backlog"
}

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:

{
  "mcpServers": {
    "backlog": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "BACKLOG_DOMAIN",
        "-e",
        "BACKLOG_API_KEY",
        "-v",
        "/yourcurrentdir/.backlog-mcp-serverrc.json:/root/.backlog-mcp-serverrc.json:ro",
        "ghcr.io/nulab/backlog-mcp-server"
      ],
      "env": {
        "BACKLOG_DOMAIN": "your-domain.backlog.com",
        "BACKLOG_API_KEY": "your-api-key"
      }
    }
  }
}

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:

docker run -i --rm ghcr.io/nulab/backlog-mcp-server node build/index.js --export-translations

or

npx github:nulab/backlog-mcp-server --export-translations

Using a Japanese Translation Template

A sample Japanese configuration file is provided at:

translationConfig/.backlog-mcp-serverrc.json.example

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 BACKLOGMCP and written in uppercase.

Example: To override the TOOL_ADD_ISSUE_COMMENT_DESCRIPTION:

{
  "mcpServers": {
    "backlog": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e", "BACKLOG_DOMAIN",
        "-e", "BACKLOG_API_KEY",
        "-e", "BACKLOG_MCP_TOOL_ADD_ISSUE_COMMENT_DESCRIPTION"
        "ghcr.io/nulab/backlog-mcp-server"
      ],
      "env": {
        "BACKLOG_DOMAIN": "your-domain.backlog.com",
        "BACKLOG_API_KEY": "your-api-key",
        "BACKLOG_MCP_TOOL_ADD_ISSUE_COMMENT_DESCRIPTION": "An alternative description"
      }
    }
  }
}

The server loads the config file synchronously at startup.

Environment variables always take precedence over the config file.