developer-tools

Port

port-labs

by port-labs

Integrate with Port.io API for AI workflow automation, enabling smarter task management and seamless workflow orchestrat

Integrates with Port.io's API to enable AI-assisted task management and workflow orchestration through authentication, prompt triggering, and response handling.

github stars

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Repository deprecated - migrate to Remote MCP ServerNatural language queries for developer portals

best for

  • / Platform engineers managing service catalogs
  • / DevOps teams tracking compliance and quality
  • / Engineering managers monitoring team ownership
  • / Developers querying internal service information

capabilities

  • / Query entity details and ownership information
  • / Check on-call status and team assignments
  • / Analyze scorecard compliance and quality metrics
  • / Create and manage scorecards with custom rules
  • / Configure action permissions and RBAC policies
  • / Retrieve catalog insights and production metrics

what it does

Connects to Port.io's developer portal API to let you query service catalogs, manage scorecards, and automate developer workflows through natural language. Note: This repository is deprecated - use Port's Remote MCP Server instead.

about

Port is a community-built MCP server published by port-labs that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate with Port.io API for AI workflow automation, enabling smarter task management and seamless workflow orchestrat It is categorized under developer tools.

how to install

You can install Port in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Port is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

⚠️ This Repository is No Longer Maintained

[!WARNING] This repository has been deprecated and is no longer actively maintained or supported. No further updates, bug fixes, or security patches will be provided.

Migrate to Port's Remote MCP Server

We strongly encourage all users to migrate to Port's Remote MCP Server, which is the actively maintained and supported solution.

The Remote MCP Server offers full feature parity and ongoing improvements backed by the Port team.


Port MCP Server

The Port IO MCP server is a Model Context Protocol (MCP) server, enabling advanced automations and natual language interactions for developers and AI applications.

What You Can Do With Port MCP

Find Information Quickly

  • Get entity details - "Who is the owner of service X?"
  • Check on-call status - "Who is on call right now?"
  • Get catalog insights - "How many services do we have in production?"

Analyze Scorecards

  • Identify weak points - "Which services are failing for the gold level and why?"
  • Get compliance status - "Show me all services that don't meet our security requirements"
  • Improve quality - "What do I need to fix to reach the next scorecard level?"

Create Resources

  • Build scorecards - "Create a new scorecard called 'Security Posture' with levels Basic, Silver, and Gold"
  • Define rules - "Add a rule that requires services to have a team owner to reach the Silver level"
  • Setup quality gates - "Create a rule that checks if services have proper documentation"

Manage Permissions & RBAC

  • Fetch action permissions - "What are the current permission settings for this action?"
  • Update action policies - "Configure approval workflows for the deployment action"
  • Configure dynamic permissions - "Set up team-based access control for this action"

We're continuously expanding Port MCP's capabilities. Have a suggestion? We'd love to hear your feedback on our roadmap!

Installation

Prerequisites

Before you begin, you'll need:

  1. Create a Port Account (if you don't have one):

    • Visit Port.io
    • Sign up for an account
  2. Obtain Port Credentials:

    • Navigate to your Port dashboard
    • Go to Settings > Credentials
    • Save both the Client ID and Client Secret
  3. Installation Requirements:

    • Either Docker installed on your system
    • OR uvx package manager installed

[!NOTE] You will also need to provide your Port region, which is either EU or US. If not provided, the default is EU.

Installation methods

Port MCP Server can be installed using two methods:

Package Installation (uvx)

Use our official Port MCP server package with uvx for easy installation and management.

Step-by-Step Installation Guide

  1. Create a Python Virtual Environment (Recommended)

    python -m venv venv
    
  2. Activate the Virtual Environment

    # On Linux/macOS:
    source venv/bin/activate
    
    # On Windows:
    venv\Scripts\activate
    
  3. Install the UV Package Manager

    # Using Homebrew (macOS/Linux):
    brew install uv
    
    # Or using pip:
    pip install uv
    
  4. Verify UV Installation

    which uv
    
  5. Set Required Environment Variables

    export PORT_CLIENT_ID="your_port_client_id"
    export PORT_CLIENT_SECRET="your_port_client_secret"
    export PORT_REGION="EU"  # or "US"
    
  6. Set Python Path (if using virtual environment)

    export PYTHONPATH="/path/to/your/venv/bin/python"
    
  7. Run the MCP Server

    uvx mcp-server-port --client-id your_port_client_id --client-secret your_port_client_secret --region EU --log-level DEBUG
    
  8. Verify Server is Running You should start seeing logs from the server. You can also check the log file:

    cat /tmp/port-mcp.log
    

Docker Installation

Use our official Docker image:

docker pull ghcr.io/port-labs/port-mcp-server:latest

See below for detailed instructions on each MCP client.

Additional configurations

You can pass these additional arguments for more advanced configuration:

Configuration ParameterUVX FlagDocker Environment VariableDescriptionDefault Value
Log Levellog-levelPORT_LOG_LEVELControls the level of log outputERROR
API Validationapi-validation-enabledPORT_API_VALIDATION_ENABLEDControls if API schema should be validated and fail if it's not validFalse

Usage with Claude Desktop

  1. Go to Settings > Developer and click on "Edit config".
  2. Edit the claude_desktop_config.json file and add the below configuration based on the installation method.
  3. Save the file and restart Claude.
  4. In a new chat, check the Tools section and you'll see Port available tools.

Claude MCP Tools

Docker

[!TIP] Consider using the full path to Docker (e.g., /usr/local/bin/docker) instead of just docker. You can find this path by running which docker in your terminal. Using the full path helps avoid PATH resolution issues and ensures consistent behavior across different shell environments.

{
  "mcpServers": {
    "port": {
      "command": "docker",
      "args": [
               "run",
                "-i",
                "--rm",
                "-e",
                "PORT_CLIENT_ID",
                "-e",
                "PORT_CLIENT_SECRET",
                "-e",
                "PORT_REGION",
                "-e",
                "PORT_LOG_LEVEL",
                "ghcr.io/port-labs/port-mcp-server:latest"
              ],
              "env": {
                "PORT_CLIENT_ID": "<PORT_CLIENT_ID>",
                "PORT_CLIENT_SECRET": "<PORT_CLIENT_SECRET>",
                "PORT_REGION": "<PORT_REGION>",
                "PORT_LOG_LEVEL": "<PORT_LOG_LEVEL>"
              }
    }
  }
}

uvx

[!NOTE] If you want to run the command from a virtual Python environment, add a PYTHONPATH variable to the env object with its path, e.g., /path/to/your/venv/bin/python.

{
  "mcpServers": {
    "Port": {
          "command": "uvx",
          "args": [
              "[email protected]",
              "--client-id",
              "<PORT_CLIENT_ID>",
              "--client-secret",
              "<PORT_CLIENT_SECRET>",
              "--region",
              "<PORT_REGION>"
          ],
          "env": {
              "PORT_CLIENT_ID": "<PORT_CLIENT_ID>",
              "PORT_CLIENT_SECRET": "<PORT_CLIENT_SECRET>",
              "PORT_REGION": "<PORT_REGION>",
              "PYTHONPATH": "/Users/matangrady/.venv-port-mcp/bin/python"
          }
      }
  }
}

Usage with Cursor

  1. Go to Cursor > Settings > Cursor Settings.
  2. Click on the MCP tab, and "Add new global MCP server".
  3. Edit the mcp.json file and add the below configuration based on the installation method.
  4. Save the file and return to Cursor Settings.
  5. You will see the new Port server and its available tools.

Cursor MCP Screenshot

Docker

[!TIP] Consider using the full path to Docker (e.g., /usr/local/bin/docker) instead of just docker. You can find this path by running which docker in your terminal. Using the full path helps avoid PATH resolution issues and ensures consistent behavior across different shell environments.

{
  "mcpServers": {
    "port": {
      "command": "docker",
      "args": [
               "run",
                "-i",
                "--rm",
                "-e",
                "PORT_CLIENT_ID",
                "-e",
                "PORT_CLIENT_SECRET",
                "-e",
                "PORT_REGION",
                "-e",
                "PORT_LOG_LEVEL",
                "ghcr.io/port-labs/port-mcp-server:latest"
              ],
              "env": {
                "PORT_CLIENT_ID": "<PORT_CLIENT_ID>",
                "PORT_CLIENT_SECRET": "<PORT_CLIENT_SECRET>",
                "PORT_REGION": "<PORT_REGION>",
                "PORT_LOG_LEVEL": "<PORT_LOG_LEVEL>"
              }
    }
  }
}

uvx

[!NOTE] If you want to run the command from a virtual Python environment, add a PYTHONPATH variable to the env object with its path, e.g., /path/to/your/venv/bin/python.

{
  "mcpServers": {
    "Port": {
          "command": "uvx",
          "args": [
              "[email protected]",
              "--client-id",
              "<PORT_CLIENT_ID>",
              "--client-secret",
              "<PORT_CLIENT_SECRET>",
              "--region",
              "<PORT_REGION>"
          ],
          "env": {
              "PORT_CLIENT_ID": "<PORT_CLIENT_ID>",
              "PORT_CLIENT_SECRET": "<PORT_CLIENT_SECRET>",
              "PORT_REGION": "<PORT_REGION>",
              "PYTHONPATH": "/Users/matangrady/.venv-port-mcp/bin/python"
          }
      }
  }
}

Usage with VS Code

[!TIP] VS Code can automatically discover MCP servers already installed in Cursor and Claude.

[!NOTE] For quick installation, use the one-click install buttons and select where to add the MCP configuration. Make sure to replace the placeholders with your Port credentials.

[Docker quick installation](https://insiders.vscode.dev/redirect/mcp/install?name=port&config=%7B%22command%22%3A%22docker%22%2C%22args%22%3A%5B%22run%22%2C%22-i%22%2C%22--rm%22%2C%22-e%22%2C%22PORT_CLIENT_ID%22%2C%22-e%22%2C%22PORT_CLIENT_SECRET%22%2C%22-e%22%2C%22PORT_REGION%22%


FAQ

What is the Port MCP server?
Port is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Port?
This profile displays 69 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.869 reviews
  • Kofi Abbas· Dec 28, 2024

    According to our notes, Port benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Daniel Garcia· Dec 28, 2024

    Useful MCP listing: Port is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Daniel Jain· Dec 28, 2024

    Port has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Kofi Verma· Dec 24, 2024

    We evaluated Port against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Dec 16, 2024

    Port is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Amelia Okafor· Dec 16, 2024

    Port is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Isabella Menon· Dec 16, 2024

    We evaluated Port against two servers with overlapping tools; this profile had the clearer scope statement.

  • Noah Perez· Dec 4, 2024

    Port reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Isabella Khanna· Nov 23, 2024

    I recommend Port for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Xiao Haddad· Nov 19, 2024

    Strong directory entry: Port surfaces stars and publisher context so we could sanity-check maintenance before adopting.

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