We strongly encourage all users to migrate to **Port's Remote MCP Server**, which is the actively maintained and supported solution.
We strongly encourage all users to migrate to Port's Remote MCP Server, which is the actively maintained and supported solution. Exposed over MCP by the port mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.
The server ships on PyPI as for, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
Everything the assistant can do here goes through one of these:
Returns — Formatted text representation of all available blueprintsYou will need 8 environment variables: PORT_CLIENT_ID, PORT_CLIENT_SECRET, PORT_REGION, PORT_LOG_LEVEL, PYTHONPATH, YOUR_PORT_CLIENT_ID, YOUR_PORT_CLIENT_SECRET, YOUR_PORT_REGION. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
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
This sits in the developer tooling group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Port's toolset — Returns — is a fair guide to whether it matches your workflow. It is maintained by port-labs; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Returns | Formatted text representation of all available blueprints |
{
"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>"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
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
| Variable | Description | Required |
|---|---|---|
| PORT_CLIENT_ID | Configuration value read at startup. | Optional |
| PORT_CLIENT_SECRET | Credential the server authenticates with. | Yes |
| PORT_REGION | Configuration value read at startup. | Optional |
| PORT_LOG_LEVEL | Configuration value read at startup. | Optional |
| PYTHONPATH | Filesystem location the server is allowed to use. | Optional |
| YOUR_PORT_CLIENT_ID | Configuration value read at startup. | Optional |
| YOUR_PORT_CLIENT_SECRET | Credential the server authenticates with. | Yes |
| YOUR_PORT_REGION | Configuration value read at startup. | Optional |
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Microsoft's official browser automation server — drive a real browser through the accessibility tree, no screenshots needed.
GitHub's official server — repos, issues, pull requests, Actions and code security, straight from your assistant.
Issue tracking at the speed of conversation — Linear's official hosted server with OAuth and zero install.
Local repository surgery — status, diffs, commits, branches and history for any repo on disk.
Timezone sanity for AI — current time anywhere and correct conversions, without the model doing date math.