Skillport MCP Server
Bring Agent Skills to Any AI Agent and Coding Agent — via CLI or MCP. Manage once, serve anywhere.
Skillport is an open-source mcp server by gotalab, written mainly in Python, with 419 GitHub stars and the MIT license. Its code was last updated Oct 25, 2026. The latest PyPI release is skillport-mcp 1.1.2, published Jun 24, 2026, with 92 downloads last week.
⚓ SkillPort
<div align="center">The SkillOps Toolkit for Agent Skills
SkillOps = Validate, manage, and deliver skills at scale.
</div>Why SkillPort?
| When you... | SkillPort... |
|---|---|
| Use a coding agent without native skill support | Serves via MCP or CLI |
| Build your own AI agent | Provides MCP server, CLI, and Python library |
| Have 50+ skills and need the right one fast | Search-first loading (Tool Search Tool pattern) |
| Check skills before deployment | Validates against the spec in CI |
| Manage skill metadata programmatically | Provides meta commands |
| Find a skill on GitHub | Installs with add <url> |
Fully compatible with the Agent Skills specification.
Features
Validate
Check skills against the Agent Skills specification.
skillport validate # Validate all skills
skillport validate ./skills # Validate specific directory
skillport validate --json # CI-friendly JSON output
Catches missing fields, naming issues, and spec violations before they cause problems.
Manage
Full lifecycle management from any source.
# Add from GitHub (shorthand)
skillport add anthropics/skills skills
# Add from GitHub (full URL)
skillport add https://github.com/anthropics/skills/tree/main/skills
# Add from local path or zip
skillport add ./my-skills
skillport add skills.zip
# Update, list, remove
skillport update # Update all from original sources
skillport list # See installed skills
skillport remove <skill-id> # Uninstall
Metadata
Update skill metadata without editing files manually. Useful for automation and keeping skills consistent across a team.
skillport meta get <skill> <key> # Get metadata value
skillport meta set <skill> <key> <val> # Set metadata value
skillport meta unset <skill> <key> # Remove metadata key
Serve
MCP server for clients that don't natively support Agent Skills.
Inspired by Anthropic's Tool Search Tool pattern — search first, load on demand:
| Tool | Purpose |
|---|---|
search_skills(query) | Find skills by description (full-text search) |
load_skill(skill_id) | Get full instructions + path |
Why search matters: With 50+ skills, loading all upfront consumes context and hurts accuracy. SkillPort loads metadata only (~100 tokens/skill), then full instructions on demand.
Works with Cursor, Copilot, Windsurf, Cline, Codex, and any MCP-compatible client.
Quick Start
Install
uv tool install skillport
# or: pip install skillport
Add Skills
# Add from GitHub
skillport add anthropics/skills skills
# Or use a custom skills directory
skillport --skills-dir .claude/skills add anthropics/skills skills
Validate
skillport validate
# ✓ All 5 skill(s) pass validation
Connect to Agents
Choose how to deliver skills to your AI agents:
| Mode | Best for | Setup |
|---|---|---|
| CLI Mode | Agents with shell access (Cursor, Windsurf, Codex, etc.) | Per-project |
| MCP Mode | MCP-compatible clients, multi-project | One-time |
CLI Mode
For agents that can run shell commands. No MCP configuration required.
skillport init # Initialize project
skillport doc # Generate AGENTS.md with skill table
skillport show <id> # Load full instructions for a skill
How it works:
skillport docgenerates a skill table in AGENTS.md- The agent reads AGENTS.md to discover available skills
- When needed, the agent runs
skillport show <id>to load full instructions
MCP Mode
For MCP-compatible clients. Install the server:
uv tool install skillport-mcp
Add to your client's config:
{
"mcpServers": {
"skillport": {
"command": "uvx",
"args": ["skillport-mcp"],
"env": { "SKILLPORT_SKILLS_DIR": "~/.skillport/skills" }
}
}
}
<details>
<summary>One-click install for popular clients</summary>
Cursor
VS Code / GitHub Copilot
Kiro
CLI Agents
# Codex
codex mcp add skillport -- uvx skillport-mcp
# Claude Code
claude mcp add skillport -- uvx skillport-mcp
</details>
Organization
Organize skills with categories and tags. Works with both CLI and MCP modes.
Categories & Tags
Use metadata to organize and filter skills:
# SKILL.md frontmatter
metadata:
skillport:
category: development
tags: [testing, quality]
alwaysApply: true # Always available (Core Skills)
Per-Client Filtering
Expose different skills to different agents:
{
"mcpServers": {
"skillport-dev": {
"command": "uvx",
"args": ["skillport-mcp"],
"env": { "SKILLPORT_ENABLED_CATEGORIES": "development,testing" }
},
"skillport-writing": {
"command": "uvx",
"args": ["skillport-mcp"],
"env": { "SKILLPORT_ENABLED_CATEGORIES": "writing,research" }
}
}
}
Configuration
| Variable | Description | Default |
|---|---|---|
SKILLPORT_SKILLS_DIR | Skills directory | ~/.skillport/skills |
SKILLPORT_ENABLED_CATEGORIES | Filter by category | all |
SKILLPORT_ENABLED_SKILLS | Filter by skill ID | all |
SKILLPORT_ENABLED_NAMESPACES | Filter by namespace | all |
SKILLPORT_CORE_SKILLS_MODE | Core Skills behavior (auto/explicit/none) | auto |
Creating Skills
Create a SKILL.md with YAML frontmatter:
---
name: my-skill
description: What this skill does
metadata:
skillport:
category: development
tags: [example]
---
# My Skill
Instructions for the AI agent.
See Creating Skills Guide for best practices.
Skill Sources
| Source | Features | Target | URL |
|---|---|---|---|
| Anthropic Official | Document skills (docx, pdf, pptx, xlsx), design, MCP builder | All users | GitHub |
| Awesome Claude Skills | Curated community collection, 2.5k+ stars | Discovery | GitHub |
| Hugging Face Skills | Dataset creation, model evaluation, LLM training, paper publishing | ML/AI engineers | GitHub |
| Claude Scientific Skills | 128+ scientific skills (bio, chem, ML), 26+ databases | Researchers | GitHub |
| ClaudeKit Skills | 30+ skills, auth, multimodal, problem-solving frameworks | Full-stack devs | GitHub |
| Superpowers | TDD, debugging, parallel agents, code review workflows | Quality-focused devs | GitHub |
| Kubernetes Operations | K8s deployment, monitoring, troubleshooting | DevOps/SRE | GitHub |
Learn More
Development
Status: Work in progress. APIs may change.
git clone https://github.com/gotalab/skillport.git
cd skillport
uv sync
# Run MCP server
SKILLPORT_SKILLS_DIR=.skills uv run skillport-mcp
# Run CLI
uv run skillport --help
# Run tests
uv run pytest
License
MIT
Local publishing credentials
Local PyPI and TestPyPI tokens are read from 1Password only by uv publish,
including its dry-run mode; builds receive no publishing credential.
Provision the ignored .env.publish-pypi and .env.publish-testpypi maps with
UV_PUBLISH_TOKEN=op://<vault>/<item>/credential; store one key per item under the publish tag.
Use make publish-check or make publish-test-check to build all three distributions and run
uv publish --dry-run without uploading. A dry-run reads the credential but does not
prove its validity or upload permissions. make publish and make publish-test perform the uploads
when explicitly requested. These local tasks require 1Password CLI and a current uv with publish dry-run support.
The GitHub Actions release workflow continues to use PyPI Trusted Publishing (OIDC).
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