Port MCP Server

An MCP server for Port.io that enables advanced automations and natural language interactions for developers and AI applications.

⚠️ This Repository is No Longer Maintained

[!WARNING]This repository has been deprecated and is no longer actively maintained or supported.No further updates, bug fixes, or security patches will be provided.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

ThePort IOMCP server is aModel Context Protocol (MCP)server, enabling advanced automations and natual language interactions for developers and AI applications.

We're continuously expanding Port MCP's capabilities. Have a suggestion? We'd love to hear your feedback on ourroadmap!
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- EitherDockerinstalled on your system
- ORuvxpackage 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.

Port MCP Server can be installed using two methods:

Use our officialPort MCP serverpackage with uvx for easy installation and management.
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# On Linux/macOS: source venv/bin/activate # On Windows: venv\Scripts\activate

# Using Homebrew (macOS/Linux): brew install uv # Or using pip: pip install uv

export PORT_CLIENT_ID="your_port_client_id" export PORT_CLIENT_SECRET="your_port_client_secret" export PORT_REGION="EU" # or "US"

export PYTHONPATH="/path/to/your/venv/bin/python"

uvx mcp-server-port --client-id your_port_client_id --client-secret your_port_client_secret --region EU --log-level DEBUG

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

[!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>" } } } }

[!NOTE] If you want to run the command from a virtual Python environment, add aPYTHONPATHvariable 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" } } } }

- Go to Cursor > Settings > Cursor Settings.
- Click on the MCP tab, and "Add new global MCP server".
- Edit themcp.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.

[!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>" } } } }

[!NOTE] If you want to run the command from a virtual Python environment, add aPYTHONPATHvariable 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" } } } }

[!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 installationuvx quick installation

[!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.

"Port": { "type": "stdio", "command": "docker", "args": [ "run", "-i", "--rm", "-e", "PORT_CLIENT_ID", "-e", "PORT_CLIENT_SECRET", "-e", "PORT_REGION", "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>" } }

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

"Port": { "type": "stdio", "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>" } }

To use Port MCP Server in Neovim, use the pluginmcphub.nvimwith one of the supported LLM extensions, such asAvanteorCodeCompanion.

Check themcphub.nvim documentationfor more details on how to use it.

[!NOTE] Make sure that you have the environment variablesPORT_CLIENT_IDandPORT_CLIENT_SECRETset with your Port credentials.

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

uvxConfiguration Example formcphub.nvim

[!NOTE] Make sure that you have the environment variablesPORT_CLIENT_IDandPORT_CLIENT_SECRETset with your Port credentials.

{ "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_SECRET": "", "PORT_REGION": "EU" } } } }

- Retrieve a list of all blueprints from Port
- Optional inputs:

- detailed(boolean, default: false): Return complete schema details for each blueprint

- Retrieve information about a specific blueprint by its identifier
- Required inputs:

- blueprint_identifier(string): The unique identifier of the blueprint to retrieve

- detailed(boolean, default: true): Return complete schema details

- Create a new blueprint in Port
- Required inputs:

- Various fields including identifier, title, properties, etc.

- Update an existing blueprint
- Required inputs:

- identifier(string): The unique identifier of the blueprint to update
- Various fields to update

- Delete a blueprint from Port
- Required inputs:

- blueprint_identifier(string): The unique identifier of the blueprint to delete

- Retrieve all entities for a given blueprint
- Required inputs:

- blueprint_identifier(string): The identifier of the blueprint to get entities for

- detailed(boolean, default: false): Return complete entity details including properties

- Retrieve information about a specific entity
- Required inputs:

- blueprint_identifier(string): The identifier of the blueprint the entity belongs to
- entity_identifier(string): The unique identifier of the entity to retrieve

- detailed(boolean, default: true): Return complete entity details

- Create a new entity for a specific blueprint
- Required inputs:

- blueprint_identifier(string): The identifier of the blueprint to create the entity for
- entity(object): The entity data following the blueprint schema

- Update an existing entity
- Required inputs:

- blueprint_identifier(string): The identifier of the blueprint the entity belongs to
- entity_identifier(string): The unique identifier of the entity to update
- entity(object): The updated entity data

- Delete an entity
- Required inputs:

- blueprint_identifier(string): The identifier of the blueprint the entity belongs to
- entity_identifier(string): The unique identifier of the entity to delete

- delete_dependents(boolean, default: false): If true, also deletes all dependencies

- Retrieve all scorecards from Port
- Optional inputs:

- detailed(boolean, default: false): Return complete scorecard details

- Retrieve information about a specific scorecard by its identifier
- Required inputs:

- scorecard_id(string): The unique identifier of the scorecard to retrieve
- blueprint_id(string, optional): The identifier of the blueprint the scorecard belongs to

- Create a new scorecard for a specific blueprint
- Required inputs:

- blueprint_id(string): The identifier of the blueprint to create the scorecard for
- identifier(string): The unique identifier for the new scorecard
- title(string): The display title of the scorecard
- levels(list): List of levels for the scorecard

- rules(list): List of rules for the scorecard
- description(string): Description for the scorecard

- Update an existing scorecard
- Required inputs:

- blueprint_identifier(string): The identifier of the blueprint the scorecard belongs to
- scorecard_identifier(string): The unique identifier of the scorecard to update
- Various fields to update (title, levels, rules, etc.)

- Delete a scorecard from Port
- Required inputs:

- blueprint_identifier(string): The identifier of the blueprint the scorecard belongs to
- scorecard_identifier(string): The unique identifier of the scorecard to delete
- invoke_ai_agent

- Invoke a Port AI agent with a specific prompt
- Required inputs:

- prompt(string): The prompt to send to the AI agent