SkillPort streamlines AI agent skill management and delivery, enabling agents without native support or handling large skill inventories. It targets developers and researchers, offering unified skill validation, lifecycle management, and on-demand serving via CLI or MCP to enhance agent capabilities and operational efficiency.

How It Works

SkillPort implements "SkillOps" for validating, managing, and delivering skills. It serves skills via the Model Context Protocol (MCP) or CLI. A key feature is its "search-first loading" pattern, which loads only skill metadata initially, deferring full instruction loading until a skill is needed. This optimizes context window usage and agent accuracy, especially for managing 50+ skills. Skills are validated against the Agent Skills specification to catch errors early.

Quick Start & Requirements

• Installation: uv tool install skillport or pip install skillport. MCP server: uv tool install skillport-mcp.
• Prerequisites: Python 3.10+. MCP compatibility.
• Resources: Links provided for one-click MCP server installation for Cursor, VS Code, and Kiro. Official docs, guides, and references are mentioned but not directly linked.

Highlighted Details

• Skill Validation: Checks skills against the Agent Skills specification, catching missing fields, naming issues, and spec violations.
• Lifecycle Management: Supports adding skills from GitHub/local paths, updating, listing, and removing them.
• Metadata Management: Programmatic updates to skill metadata (categories, tags) for organization and filtering.
• Flexible Serving: Offers CLI mode for shell-access agents and MCP mode for MCP-compatible clients.
• Search-First Loading: Optimizes performance by loading only skill metadata (~100 tokens/skill) initially, fetching full instructions on demand.

Maintenance & Community

No specific details regarding maintainers, community channels (like Discord/Slack), or active sponsorships are present in the provided README.

Licensing & Compatibility

• License: MIT License.
• Compatibility: Designed for MCP-enabled AI agents and clients (Cursor, VS Code, Windsurf, Cline, Codex, Kiro). The MIT license permits commercial use and integration into closed-source projects.

Limitations & Caveats

The project is explicitly marked as "Work in progress," indicating that its APIs are subject to change, which could impact stability and require ongoing maintenance for adopters.