Port▌

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.
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⚠️ This Repository is No Longer Maintained
[!WARNING] This repository has been deprecated and is no longer actively maintained or supported.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:
-
Create a Port Account (if you don't have one):
- Visit Port.io
- Sign up for an account
-
Obtain Port Credentials:
- Navigate to your Port dashboard
- Go to Settings > Credentials
- Save both the Client ID and Client Secret
-
Installation Requirements:
[!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
-
Create a Python Virtual Environment (Recommended)
python -m venv venv -
Activate the Virtual Environment
# On Linux/macOS: source venv/bin/activate # On Windows: venv\Scripts\activate -
Install the UV Package Manager
# Using Homebrew (macOS/Linux): brew install uv # Or using pip: pip install uv -
Verify UV Installation
which uv -
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" -
Set Python Path (if using virtual environment)
export PYTHONPATH="/path/to/your/venv/bin/python" -
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 -
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 Parameter | UVX Flag | Docker Environment Variable | Description | Default Value |
|---|---|---|---|---|
| Log Level | log-level | PORT_LOG_LEVEL | Controls the level of log output | ERROR |
| API Validation | api-validation-enabled | PORT_API_VALIDATION_ENABLED | Controls if API schema should be validated and fail if it's not valid | False |
Usage with Claude Desktop
- Go to Settings > Developer and click on "Edit config".
- Edit the
claude_desktop_config.jsonfile and add the below configuration based on the installation method. - Save the file and restart Claude.
- In a new chat, check the Tools section and you'll see Port available tools.

Docker
[!TIP] Consider using the full path to Docker (e.g.,
/usr/local/bin/docker) instead of justdocker. You can find this path by runningwhich dockerin 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
PYTHONPATHvariable to theenvobject with its path, e.g.,/path/to/your/venv/bin/python.
{
"mcpServers": {
"Port": {
"command": "uvx",
"args": [
"mcp-server-port@0.2.8",
"--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
- Go to Cursor > Settings > Cursor Settings.
- Click on the MCP tab, and "Add new global MCP server".
- Edit the
mcp.jsonfile and add the below configuration based on the installation method. - Save the file and return to Cursor Settings.
- You will see the new Port server and its available tools.

Docker
[!TIP] Consider using the full path to Docker (e.g.,
/usr/local/bin/docker) instead of justdocker. You can find this path by runningwhich dockerin 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
PYTHONPATHvariable to theenvobject with its path, e.g.,/path/to/your/venv/bin/python.
{
"mcpServers": {
"Port": {
"command": "uvx",
"args": [
"mcp-server-port@0.2.8",
"--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.
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 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Ratings
4.5★★★★★10 reviews- ★★★★★Shikha Mishra· Oct 10, 2024
Port is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Piyush G· Sep 9, 2024
We evaluated Port against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Chaitanya Patil· Aug 8, 2024
Useful MCP listing: Port is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Sakshi Patil· Jul 7, 2024
Port reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Ganesh Mohane· Jun 6, 2024
I recommend Port for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Oshnikdeep· May 5, 2024
Strong directory entry: Port surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Dhruvi Jain· Apr 4, 2024
Port has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Rahul Santra· Mar 3, 2024
According to our notes, Port benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Pratham Ware· Feb 2, 2024
We wired Port into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Yash Thakker· Jan 1, 2024
Port is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.