Skillport MCP Server

by gotalab• 419•• Scanned•Claim this listing•Request removal
Coding Agentsagent skillsai agentclaudecodexcontext engineering

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.

Python MCP License

</div>

Why SkillPort?

When you...SkillPort...
Use a coding agent without native skill supportServes via MCP or CLI
Build your own AI agentProvides MCP server, CLI, and Python library
Have 50+ skills and need the right one fastSearch-first loading (Tool Search Tool pattern)
Check skills before deploymentValidates against the spec in CI
Manage skill metadata programmaticallyProvides meta commands
Find a skill on GitHubInstalls 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:

ToolPurpose
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:

ModeBest forSetup
CLI ModeAgents with shell access (Cursor, Windsurf, Codex, etc.)Per-project
MCP ModeMCP-compatible clients, multi-projectOne-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:

  1. skillport doc generates a skill table in AGENTS.md
  2. The agent reads AGENTS.md to discover available skills
  3. 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

Install MCP Server

VS Code / GitHub Copilot

Install in VS Code

Kiro

Add to 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

VariableDescriptionDefault
SKILLPORT_SKILLS_DIRSkills directory~/.skillport/skills
SKILLPORT_ENABLED_CATEGORIESFilter by categoryall
SKILLPORT_ENABLED_SKILLSFilter by skill IDall
SKILLPORT_ENABLED_NAMESPACESFilter by namespaceall
SKILLPORT_CORE_SKILLS_MODECore 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

SourceFeaturesTargetURL
Anthropic OfficialDocument skills (docx, pdf, pptx, xlsx), design, MCP builderAll usersGitHub
Awesome Claude SkillsCurated community collection, 2.5k+ starsDiscoveryGitHub
Hugging Face SkillsDataset creation, model evaluation, LLM training, paper publishingML/AI engineersGitHub
Claude Scientific Skills128+ scientific skills (bio, chem, ML), 26+ databasesResearchersGitHub
ClaudeKit Skills30+ skills, auth, multimodal, problem-solving frameworksFull-stack devsGitHub
SuperpowersTDD, debugging, parallel agents, code review workflowsQuality-focused devsGitHub
Kubernetes OperationsK8s deployment, monitoring, troubleshootingDevOps/SREGitHub

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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