mcporter
OfficialList, configure, authenticate, call, and inspect MCP servers/tools with mcporter over HTTP or stdio.
What this skill does
When applied, it prepends a system prompt before your request is sent — no extra calls and no change to how you are billed beyond the added tokens.
---
name: mcporter
description: "List, configure, authenticate, call, and inspect MCP servers/tools with mcporter over HTTP or stdio."
homepage: http://mcporter.dev
metadata:
{
"openclaw":
{
"emoji": "📦",
"requires": { "bins": ["mcporter"] },
"install":
[
{
"id": "node",
"kind": "node",
"package": "mcporter",
"bins": ["mcporter"],
"label": "Install mcporter (node)",
},
],
},
}
---
# mcporter
Use `mcporter` to work with MCP servers directly.
Quick start
- `mcporter list`
- `mcporter list <server> --schema`
- `mcporter call <server.tool> key=value`
Call tools
- Selector: `mcporter call linear.list_issues team=ENG limit:5`
- Function syntax: `mcporter call "linear.create_issue(title: \"Bug\")"`
- Full URL: `mcporter call https://api.example.com/mcp.fetch url:https://example.com`
- Stdio: `mcporter call --stdio "bun run ./server.ts" scrape url=https://example.com`
- JSON payload: `mcporter call <server.tool> --args '{"limit":5}'`
Auth + config
- OAuth: `mcporter auth <server | url> [--reset]`
- Config: `mcporter config list|get|add|remove|import|login|logout`
Daemon
- `mcporter daemon start|status|stop|restart`
Codegen
- CLI: `mcporter generate-cli --server <name>` or `--command <url>`
- Inspect: `mcporter inspect-cli <path> [--json]`
- TS: `mcporter emit-ts <server> --mode client|types`
Notes
- Config default: `./config/mcporter.json` (override with `--config`).
- Prefer `--output json` for machine-readable results.
Use this skill
Add a "skill" field with the skill’s ID to your chat completion request. It is applied server-side before your prompt is sent — no extra calls.
{
"model": "gpt-4o-mini",
"skill": "imp-7732a26e-c453-4862-b04d-883e98a195ba",
"messages": [{ "role": "user", "content": "…" }]
}Install the skill, enable it in your dashboard and (optionally) limit it to specific models. It then applies automatically to every matching request — with no "skill" field to send each time.
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