ZenHub

About this Protocol

This ZenHub MCP server acts as a bridge between AI assistants and the ZenHub project management platform. It allows Large Language Models (LLMs) to understand and interact with project workflows, making it much easier for teams to keep track of their development progress without constantly switching between different applications. By connecting an AI directly to ZenHub, developers can use natural language to ask about project status, update task lists, or organize their daily work through a simple chat interface. The server provides a robust set of 54 specialized tools that cover the most essential project management tasks across ten different categories. It empowers an AI to create GitHub issues, manage epics, set story point estimates, and organize sprints across various workspaces. It also supports complex filtering and searching, allowing the AI to locate specific issues within pipelines and even reassign tasks or add labels on the fly. This level of integration transforms a standard AI assistant into a functional project coordinator that can handle the routine maintenance of project tickets. For more technical implementations, this tool provides direct access to the ZenHub GraphQL API, including a flexible query tool for executing custom GraphQL strings and variables. It is built on a modular architecture designed for easy expansion, currently covering approximately 30% of ZenHub’s total available operations. Security is managed through API key-based authentication via environment variables, and the server is fully compatible with professional AI environments like Claude Desktop and Cursor. This deep technical integration ensures that AI systems have the precision required to execute complex data mutations and retrieve nested project metadata with high reliability.

How to Use

1. Installation

To install the ZenHub MCP server for development or manual setup, run the following commands in the project directory:

npm install
npm run build

API Key Setup:
1. Obtain your ZenHub API key from ZenHub Settings.
2. Set the environment variable:
bash export ZENHUB_API_KEY=your_api_key_here
Alternatively, create a .env file by copying .env.example and adding your key.

2. Configuration

For Claude Desktop

Add the following to your Claude Desktop configuration file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "zenhub": {
      "command": "npx",
      "args": ["zenhub-mcp-server"],
      "env": {
        "ZENHUB_API_KEY": "your_api_key_here"
      }
    }
  }
}

For Cursor

Go to Settings > MCP Servers and add the following configuration:

{
  "name": "zenhub",
  "command": "node",
  "args": ["/path/to/zenhub-mcp/dist/index.js"],
  "env": {
    "ZENHUB_API_KEY": "your_api_key_here",
    "GITHUB_PAT": "your_github_pat_here"
  }
}

Alternatively, for development mode in Cursor:

{
  "name": "zenhub-dev",
  "command": "npm",
  "args": ["run", "dev"],
  "cwd": "/path/to/zenhub-mcp",
  "env": {
    "ZENHUB_API_KEY": "your_api_key_here"
  }
}

3. Available Tools

The server provides 54 tools. Key tools include:

Query Tools
* zenhub_query: Execute any GraphQL query against the ZenHub API.
* zenhub_search_issues: Search for issues in a specific pipeline.
* zenhub_search_issues_in_repository: Search and filter issues inside a repository.
* zenhub_get_workspace_issues: Get all issues in a workspace (paginated).
* zenhub_get_viewer: Get current ZenHub user information.
* zenhub_get_issue_by_info: Lookup an issue by repository and issue number.
* zenhub_get_repositories: Lookup repositories by their GitHub IDs.

Issue Management
* zenhub_create_issue: Create a new GitHub issue via ZenHub.
* zenhub_close_issues: Close one or more issues.
* zenhub_reopen_issues: Reopen closed issues and move to a specific pipeline.
* zenhub_move_issue: Move issues to a specific pipeline and position.
* zenhub_add_assignees_to_issues: Add assignees to multiple issues.
* zenhub_add_labels_to_issues: Add labels to multiple issues.
* zenhub_set_estimate: Set an estimate for an issue.
* zenhub_add_issues_to_epics: Add issues to epics.

Epic Management
* zenhub_create_epic: Create a new epic in ZenHub.

Workspace Management
* zenhub_get_user_workspaces: Get all workspaces accessible to the user.
* zenhub_get_user_organizations: Get accessible ZenHub organizations.
* zenhub_create_workspace: Create a new workspace.

Sprint Management
* zenhub_create_sprint: Create a new sprint with specific dates.
* zenhub_add_issues_to_sprints: Add issues to specific sprints.

4. Example Prompts

No specific example prompts were provided in the content.

Use Cases

Use Case 1: Automated Sprint Transition and Cleanup

Problem: At the end of a development cycle, project managers often spend significant time manually moving incomplete issues to the next sprint, closing out finished tasks, and creating the next sprint container.
Solution: This MCP allows an AI assistant to automate the "Sprint Handover." The AI can identify all open issues in the current sprint, create a new sprint with appropriate dates, and move the unfinished work items in one go.
Example: "Look at my current workspace. Find all issues that are still 'In Progress' or 'Review' in the current sprint, create a new sprint called 'Sprint 24' starting next Monday, and move those issues into it."

Use Case 2: AI-Powered Issue Triaging and Bulk Estimation

Problem: During planning sessions, teams often have dozens of new, "raw" GitHub issues that lack labels, estimates, or assignees. Manually updating each one through the UI is tedious and prone to inconsistency.
Solution: Using the zenhub_set_multiple_estimates and zenhub_add_labels_to_issues tools, an AI can analyze the content of multiple issues simultaneously and apply standardized metadata based on the project's history or team guidelines.
Example: "Analyze the last 10 issues created in the 'Backend' repository. Based on their descriptions, suggest complexity estimates, apply the 'bug' or 'feature' labels, and assign the 'API-related' issues to @dev_lead."

Use Case 3: Transforming Feature Requests into Structured Epics

Problem: Product managers often have a high-level feature concept that needs to be broken down into a ZenHub Epic with several child issues. Mapping these relationships manually in the UI requires multiple steps for every sub-task.
Solution: The AI can take a long-form feature description, use zenhub_create_epic to establish the parent container, create the individual task issues, and then use zenhub_add_issues_to_epics to link them all together instantly.
Example: "I want to build a new 'User Dashboard.' Create an Epic for this in the 'Web-App' repo. Then, create three issues for the UI, the Auth integration, and the API endpoints, and add all of them to that new Epic."

Use Case 4: Intelligent Workflow Health Audits

Problem: Bottlenecks in the development pipeline (e.g., too many issues stuck in 'Code Review') are hard to visualize and summarize without manual investigation of the ZenHub board.
Solution: By using zenhub_get_workspace_issues and zenhub_query, an AI assistant can perform a "health check" on the workspace. It can identify pipelines that are overloaded and suggest reassignments or movements to keep the flow moving.
Example: "Scan the 'Mobile App' workspace and tell me if any pipeline has more than 5 issues. If the 'Review' pipeline is blocked, list the oldest issues there and summarize who is assigned to them so we can discuss it in the standup."

Use Case 5: Cross-Repository Workspace Bootstrapping

Problem: When starting a large-scale project that spans multiple microservices, setting up a unified ZenHub workspace to track all those repositories is a multi-click configuration process.
Solution: A developer can use the zenhub_create_workspace tool via the AI to instantly bundle multiple GitHub repository IDs into a single, cohesive ZenHub environment with a defined organization and default repository.
Example: "Create a new ZenHub workspace called 'Project Phoenix' under the 'Engineering' organization. Include the repositories for 'phoenix-api', 'phoenix-frontend', and 'phoenix-docs', and set the API repo as the default."

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Added Dec 27, 2025