Productboard MCP Server

What does “Productboard” MCP Server do?

The Productboard MCP (Model Context Protocol) Server acts as a bridge between AI assistants and the Productboard API, enabling seamless integration of product management data into agentic workflows. By exposing Productboard’s functionality through MCP, this server allows AI-driven tools and agents to interact programmatically with features, components, companies, and notes in Productboard. This enhances development and product management workflows by automating data queries, retrieving product insights, and integrating with broader systems that rely on contextual product information. Developers and teams can leverage this integration to streamline tasks such as fetching product features, managing product components, or accessing company-related information, all within their preferred AI-driven platforms.

List of Prompts

No prompt templates are mentioned in the provided repository.

List of Resources

No explicit resources are listed in the available documentation or repository files.

List of Tools

• get_companies: Retrieves a list of companies from Productboard.
• get_company_detail: Fetches detailed information about a specific company.
• get_components: Retrieves a list of product components.
• get_component_detail: Provides detailed information about a specific component.
• get_features: Lists product features available in Productboard.
• get_feature_detail: Fetches detailed information about a specific product feature.
• get_feature_statuses: Retrieves the statuses of various features.
• get_notes: Lists notes associated with products or features.
• get_products: Retrieves a list of products from Productboard.
• get_product_detail: Fetches detailed information about a specific product.

Use Cases of this MCP Server

• Product Feature Exploration: Developers and product managers can quickly fetch and analyze details about product features, including their statuses and associated notes, to make informed prioritization decisions.
• Company Data Aggregation: Teams can automate the retrieval of company and customer information, aiding in customer insights and relationship management.
• Component Management: Facilitates the exploration and management of product components, helping to streamline architecture or roadmap planning.
• Product Overview Generation: Automated generation of product overviews and summaries by retrieving lists and details of products directly from Productboard.
• Workflow Automation: Enables integration with agentic platforms to automate repetitive Productboard queries, reducing manual effort for product operations teams.

How to set it up

Windsurf

No setup instructions for Windsurf are present in the repository.

Claude

1. Prerequisite: Obtain your Productboard access token (authentication guide).
2. Open your claude_desktop_config.json configuration file.
3. Add the Productboard MCP Server to the mcpServers section using NPX.
4. Insert the following configuration snippet (replace <YOUR_TOKEN> with your access token):

   {
     "mcpServers": {
       "productboard": {
         "command": "npx",
         "args": [
           "-y",
           "productboard-mcp"
         ],
         "env": {
           "PRODUCTBOARD_ACCESS_TOKEN": "<YOUR_TOKEN>"
         }
       }
     }
   }
   

5. Save the file and restart Claude Desktop.
6. Verify that the Productboard MCP Server is available in your MCP tool list.

Cursor

No setup instructions for Cursor are present in the repository.

Cline

No setup instructions for Cline are present in the repository.

Securing API Keys

To secure your Productboard API key, use environment variables as shown in the configuration snippet above. Do not hardcode sensitive credentials directly in your configuration files.

Example:

"env": {
  "PRODUCTBOARD_ACCESS_TOKEN": "<YOUR_TOKEN>"
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "productboard": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “productboard” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the two tables, Productboard MCP provides strong basic tooling and clear setup for Claude, but is lacking in prompt templates, resources, and documentation for other platforms. There is no mention of Roots or Sampling support. I would rate this MCP server a 5/10 for general agentic workflow integration, primarily for its tool completeness and open licensing, but with notable gaps in documentation and advanced MCP features.

MCP Score