Skilljack MCP
An MCP server that jacks Agent Skills directly into your LLM's brain.
Recommended: For best results, use an MCP client that supports
tools/listChangednotifications (e.g., Claude Code). This enables dynamic skill discovery - when skills are added or modified, the client automatically refreshes its understanding of available skills.
Features
- Dynamic Skill Discovery - Watches skill directories and automatically refreshes when skills change
- Tool List Changed Notifications - Sends
tools/listChangedso clients can refresh available skills - Skill Tool - Load full skill content on demand (progressive disclosure)
- MCP Prompts - Load skills via
/skillprompt with auto-completion or per-skill prompts - MCP Resources - Access skills via
skill://URIs with batch collection support - Resource Subscriptions - Real-time file watching with
notifications/resources/updated
Motivation
This repo demonstrates a way to approach integrating skills using existing MCP primitives.
MCP already has the building blocks:
- Tools for on-demand skill loading (the
skilltool with dynamically updated descriptions) - Resources for explicit skill access (
skill://URIs) - Notifications for real-time updates (
tools/listChanged,resources/updated) - Prompts for explicitly invoking skills by name (
/my-server-skill)
This approach provides separation of concerns. Rather than every MCP server needing to embed skill handling, the server acts as a dedicated 'skill gateway'. Server authors can bundle skills alongside their MCP servers without modifying the servers themselves. If MCP registries support robust tool discovery, skill tools become discoverable like any other tool.
Installation
npm install @skilljack/mcp
Or run directly with npx:
npx @skilljack/mcp /path/to/skills
From Source
git clone https://github.com/olaservo/skilljack-mcp.git
cd skilljack-mcp
npm install
npm run build
Usage
Configure one or more skills directories containing your Agent Skills:
# Single directory
skilljack-mcp /path/to/skills
# Multiple directories (separate args or comma-separated)
skilljack-mcp /path/to/skills /path/to/more/skills
skilljack-mcp /path/to/skills,/path/to/more/skills
# Using environment variable (comma-separated for multiple)
SKILLS_DIR=/path/to/skills skilljack-mcp
SKILLS_DIR=/path/to/skills,/path/to/more/skills skilljack-mcp
Each directory is scanned along with its .claude/skills/ and skills/ subdirectories for skills. Duplicate skill names are handled by keeping the first occurrence.
Windows note: Use forward slashes in paths when using with MCP Inspector:
skilljack-mcp "C:/Users/you/skills"
How It Works
The server implements the Agent Skills progressive disclosure pattern with dynamic updates:
- At startup: Discovers skills from configured directories and starts file watchers
- On connection: Skill tool description includes available skills metadata
- On file change: Re-discovers skills, updates tool description, sends
tools/listChanged - On tool call: Agent calls
skilltool to load full SKILL.md content - As needed: Agent calls
skill-resourceto load additional files
┌─────────────────────────────────────────────────────────┐
│ Server starts │
│ • Discovers skills from configured directories │
│ • Starts watching for SKILL.md changes │
│ ↓ │
│ MCP Client connects │
│ • Skill tool description includes available skills │
│ • Prompts registered for each skill │
│ ↓ │
│ LLM sees skill metadata in tool description │
│ ↓ │
│ SKILL.md added/modified/removed │
│ • Server re-discovers skills │
│ • Updates skill tool description │
│ • Updates prompt list (add/remove/modify) │
│ • Sends tools/listChanged notification │
│ • Sends prompts/listChanged notification │
│ • Client refreshes tool and prompt definitions │
│ ↓ │
│ User invokes /skill prompt or /skill-name prompt │
│ OR LLM calls "skill" tool with skill name │
│ ↓ │
│ Server returns full SKILL.md content │
│ ↓ │
│ LLM calls "skill-resource" for additional files │
│ • Scripts, snippets, references, assets, etc. │
└─────────────────────────────────────────────────────────┘
Tools vs Resources vs Prompts
This server exposes skills via tools, resources, and prompts:
- Tools (
skill,skill-resource) - For your agent to use autonomously. The LLM sees available skills in the tool description and calls them as needed. - Prompts (
/skill,/skill-name) - For explicit user invocation. Use/skillwith auto-completion or select a skill directly by name. - Resources (
skill://URIs) - For manual selection in apps that support it (e.g., Claude Desktop's resource picker). Useful when you want to explicitly attach a skill to the conversation.
Most users will rely on tools for automatic skill activation. Prompts provide user-initiated loading with auto-completion. Resources provide an alternative for manual control.
Progressive Disclosure Design
This server implements the Agent Skills progressive disclosure pattern, which structures skills for efficient context usage:
| Level | Tokens | What's loaded | When |
|---|---|---|---|
| Metadata | ~100 | name and description | At startup, for all skills |
| Instructions | < 5000 | Full SKILL.md body | When skill is activated |
| Resources | As needed | Files in scripts/, references/, assets/ | On demand via skill-resource |
How it works
- Discovery - Server loads metadata from all skills into the
skilltool description - Activation - When a skill is loaded (via tool, prompt, or resource), only the SKILL.md content is returned
- Execution - SKILL.md references additional files; agent fetches them with
skill-resourceas needed
Why SKILL.md documents its own resources
The server doesn't automatically list all files in a skill directory. Instead, skill authors document available resources directly in their SKILL.md (e.g., "Copy the template from templates/server.ts"). This design choice follows the spec because:
- Skill authors know best - They decide which files are relevant and when to use them
- Context efficiency - Loading everything upfront wastes tokens on files the agent may not need
- Natural flow - SKILL.md guides the agent through resources in a logical order
For skill authors: Reference files using relative paths from the skill root (e.g., snippets/tool.ts, references/api.md). Keep your main SKILL.md under 500 lines; move detailed reference material to separate files. See the Agent Skills specification for complete authoring guidelines.
Tools
skill
Load and activate an Agent Skill by name. Returns the full SKILL.md content.
Input:
{
"name": "skill-name"
}
Output: Full SKILL.md content including frontmatter and instructions.
skill-resource
Read files within a skill's directory (scripts/, references/, assets/, snippets/, etc.).
This follows the Agent Skills spec's progressive disclosure pattern - resources are loaded only when needed.
Read a single file:
{
"skill": "mcp-server-ts",
"path": "snippets/tools/echo.ts"
}
Read all files in a directory:
{
"skill": "algorithmic-art",
"path": "templates"
}
Returns all files in the directory as multiple content items.
List available files (pass empty path):
{
"skill": "mcp-server-ts",
"path": ""
}
Security: Path traversal is prevented - only files within the skill directory can be accessed.
Prompts
Skills can be loaded via MCP Prompts for explicit user invocation.
/skill Prompt
Load a skill by name with auto-completion support.
Arguments:
name(string, required) - Skill name with auto-completion
The prompt description includes all available skills for discoverability. As you type the skill name, matching skills are suggested.
Per-Skill Prompts
Each discovered skill is also registered as its own prompt (e.g., /mcp-server-ts, /algorithmic-art).
- No arguments needed - just select and invoke
- Description shows the skill's own description
- List updates dynamically as skills change
Example: If you have a skill named mcp-server-ts, you can invoke it directly as /mcp-server-ts.
Content Annotations
Prompt responses include MCP content annotations for proper handling:
audience: ["assistant"]- Content is intended for the LLM, not the userpriority: 1.0- High priority content that should be included in context
Prompts return embedded resources with the skill's skill:// URI, allowing clients to track the content source.
Resources
Skills are also accessible via MCP Resources using skill:// URIs.
URI Patterns
| URI | Returns |
|---|---|
skill://{name} | Single skill's SKILL.md content |
skill://{name}/ | All files in skill directory (collection) |
Individual file URIs (skill://{name}/{path}) are not listed as resources to reduce noise. Use the skill-resource tool to fetch specific files on demand.
Resource Subscriptions
Clients can subscribe to resources for real-time updates when files change.
Capability: resources: { subscribe: true, listChanged: true }
Subscribe to a resource:
→ resources/subscribe { uri: "skill://mcp-server-ts" }
← {} (success)
Receive notifications when files change:
← notifications/resources/updated { uri: "skill://mcp-server-ts" }
Unsubscribe:
→ resources/unsubscribe { uri: "skill://mcp-server-ts" }
← {} (success)
How it works:
- Client subscribes to a
skill://URI - Server resolves URI to file path(s) and starts watching with chokidar
- When files change, server debounces (100ms) and sends notification
- Client can re-read the resource to get updated content
Security
Skills are treated as trusted content. This server reads and serves skill files directly to clients without sanitization. Only configure skills directories containing content you trust.
Protections in place:
- Path traversal prevention (symlink-aware)
- File size limits (1MB default, configurable via
MAX_FILE_SIZE_MBenv var) - Directory depth limits
- Skill content is confined to configured directories
Not protected against:
- Malicious content within trusted skill directories
- Prompt injection via skill instructions (skills can influence LLM behavior by design)
Dynamic Skill Discovery
The server watches skill directories for changes. When SKILL.md files are added, modified, or removed:
- Skills are re-discovered from all configured directories
- The
skilltool's description is updated with current skill names and metadata - Per-skill prompts are added, removed, or updated accordingly
tools/listChangedandprompts/listChangednotifications are sent to connected clients- Clients that support these notifications will refresh tool and prompt definitions
Skill Metadata Format
The skill tool description includes metadata for all available skills in XML format:
# Skills
When a user's task matches a skill description below: 1) activate it, 2) follow its instructions completely.
<available_skills>
<skill>
<name>mcp-server-ts</name>
<description>Build TypeScript MCP servers with composable code snippets...</description>
<location>C:/path/to/mcp-server-ts/SKILL.md</location>
</skill>
</available_skills>
This metadata is dynamically updated when skills change - clients supporting tools/listChanged will automatically refresh.
Skill Discovery
Skills are discovered at startup from the configured directories. For each directory, the server checks:
- The directory itself for skill subdirectories
.claude/skills/subdirectoryskills/subdirectory
Each skill subdirectory must contain a SKILL.md file with YAML frontmatter including name and description fields.
Testing
Manual Testing with MCP Inspector
npm run build
npm run inspector -- /path/to/skills
Automated Evals (Development Only)
The evals/ directory contains an evaluation framework for testing skill activation across different delivery modes. Evals are only available when developing from source (not included in the npm package).
# Clone the repo first
git clone https://github.com/olaservo/skilljack-mcp.git
cd skilljack-mcp
# Install dev dependencies (includes claude-agent-sdk for evals)
npm install
# Build and run evals
npm run build
npm run eval # Default: greeting task, MCP mode
npm run eval -- --task=xlsx-openpyxl # Specific task
npm run eval -- --mode=native # Native skill mode
npm run eval -- --mode=mcp+native # Both MCP and native enabled
See evals/README.md for details on available tasks, modes, and findings about activation behavior differences.