Provider agnostic skills implementation, with skills sourced from local paths or GitHub repositories
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Emulate Claude Skills with any LLM via a Model Context Protocol (MCP) server.
Skills are modular components that enhance the capabilities of an MCP-compatible agent by providing specific functionalities, workflows, and domain expertise. They transform a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.
The goal is to be fully compatible with Anthropic's skill format. See their Agent Skills Spec and related documentation for more details.
Skills are modular, self-contained packages that extend agent capabilities by providing specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific domains or tasksβthey transform the agent from a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.
Every skill consists of a required SKILL.md file and optional bundled resources:
Metadata Quality: The name and description in YAML frontmatter determine when the agent will use the skill. Be specific about what the skill does and when to use it. Use the third-person (e.g. "This skill should be used when..." instead of "Use this skill when...").
scripts/)Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.
scripts/rotate_pdf.py for PDF rotation tasksreferences/)Documentation and reference material intended to be loaded as needed into context to inform the agent's process and thinking.
references/finance.md for financial schemas, references/mnda.md for company NDA template, references/policies.md for company policies, references/api_docs.md for API specificationsassets/)Files not intended to be loaded into context, but rather used within the output the agent produces.
assets/logo.png for brand assets, assets/slides.pptx for PowerPoint templates, assets/frontend-template/ for HTML/React boilerplate, assets/font.ttf for typographySkills use a three-level loading system to manage context efficiently:
*Unlimited because scripts can be executed without reading into context window.
SKILLS_FILE: Path to the YAML file configuring the set of skills. Default: ./skills.yamlSKILLS_TTL: Time (in milliseconds) to cache loaded skills. Default: 5 minutesThe set of skills is configured via a YAML file. Both local directories and GitHub repositories are supported. Config can point to individual skills or collections of skills.
Skill names must be unique across all configured skills. Any duplicates will be ignored with a warning.
Individual clients can control the set of skills that are enabled, as well as the protocol(s) used, via parameters in the connection string.
enabled_skills: Comma-separated list of skill keys to enable. If not provided, all configured skills are enabled.disabled_skills: Comma-separated list of skill keys to disable. If not provided, no skills are disabled.tools=0: Disable all tools (for resource-only integration).resources=0: Disable all resources (for tool-only integration).This MCP server (optionally) provides a subagent tool that can be used to break up complex tasks into smaller subtasks, each handled by its own agent instance. This is useful for tasks that require multiple steps, especially when those steps may require consuming large amounts of data in LLM context.
The subagent will automatically have access to the same set of skills as configured for the view skill tool, as well as the ability to (recursively) invoke further subagents. In addition, a mcp.yaml configuration file can be provided to specify additional tooling to be made available to the subagent.
If you do not wish to use subagents, you can set SUBAGENT_DISABLED=true in the environment to disable the tool.
Create a mcp.yaml file to specify additional tools for the subagent to have accessible. This file is read from the root directory by default, or you can specify a different path via the MCP_PATH environment variable.
Only the streamable HTTP transport is supported at this time.
Cloning and running the server locally.
Run ./bun i to install dependencies and build the project. Use ./bun watch to rebuild on changes.
You will need a GitHub token with the correct scopes. Here is a direct link to create such a new token.
Create a .env file based on the .env.sample file.
Then update the GITHUB_TOKEN value in .env.
The MCP Inspector is a very handy to exercise the MCP server from a web-based UI.
| Field | Value |
|---|---|
| Transport Type | Streamable HTTP |
| URL | http://localhost:3001/mcp |
| Field | Value |
|---|---|
| Transport Type | STDIO |
| Command | node |
| Arguments | dist/index.js |
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