Hierarchical Skills For AI Server
БесплатноНе проверенA hierarchical MCP server for managing skill definitions with a browsable tree structure and full-text search. It allows AI agents to efficiently discover and u
Описание
A hierarchical MCP server for managing skill definitions with a browsable tree structure and full-text search. It allows AI agents to efficiently discover and use skills without consuming context tokens.
README
A hierarchical MCP (Model Context Protocol) server for managing skill definitions. Skills are stored as folders containing SKILL.md with YAML frontmatter, organized in a browsable tree structure with full-text search and a web UI.
When to Use / When Not to Use
Use this when
- You have many skills (100+) and including all their frontmatter in the AI's context window would waste tokens
- You want structured, hierarchical organization of skills by domain (coding, security, writing...)
- You want search + browse so the AI can find the right skill without knowing the exact path
- You want usage tracking so popular skills naturally rank higher over time
- You want a web UI for humans to browse the same skill tree
Don't use this when
- You have few skills (< 15) — just install them as per your agents' instructions, no server needed
- Your skills are ephemeral or one-shot — the server setup overhead isn't worth it
- You need real-time editing or CRUD from the web UI — it's read-only by design
- You need multi-user auth or permissions — not built for that
- You need relational queries or a database backend — this is filesystem + in-memory index
Architecture
Agent (MCP client) Human (browser)
↓ ↓
Skills MCP Server ← python mcp_server.py --port 8080
│ │
├── MCP (stdio) ├── HTTP (web UI)
│ browse(path, depth=1) │ GET /api/browse?path=&depth=
│ read(path) │ GET /api/search?q=
│ search(query) │ GET /api/read?path=
│ info(path) │ GET /api/info?path=
│ use(path) │
│ steps(path) │
│ reload() │
│ │
└──────────────────────────────┘
↓
┌───────────┼───────────┐
↓ ↓ ↓
File system Index Usage stats
(SKILL.md) (tags, (uses count,
aliases, last_used)
body,
relations)
Quick Start
# Install
python3 -m venv venv
source venv/bin/activate
pip install -e .
# Run with sample skills (activate venv first)
python mcp_server.py --port 8080
# Open web UI
open http://localhost:8080
CLI Arguments
| Argument | Required | Default | Description |
|---|---|---|---|
--repo |
No | sample_skills |
Path to root folder containing grouped skills |
--max-depth |
No | 4 | Maximum folder depth to walk |
--port |
No | 8080 | Port for web UI |
--host |
No | localhost | Host for web UI |
MCP Tools
| Tool | Input | Output | Description |
|---|---|---|---|
browse(path, depth=1) |
"", "coding", "coding/python" |
Child groups + skills (nested if depth>1) |
Navigate the skill hierarchy |
read(path) |
"coding/python/fastapi" |
Full SKILL.md body | Load skill content |
search(query) |
"fastapi", "web" |
Ranked paths | Search by name, tags, aliases, description, path segments |
info(path) |
"coding/python/fastapi" |
YAML metadata (no body) | Lightweight skill inspection |
use(path) |
"coding/python/fastapi" |
Updated metadata | Track skill usage (boosts search ranking) |
steps(path) |
"coding/python/fastapi" |
Ordered step list | Get workflow sub-skills |
reload() |
— | Status | Re-scan repo, re-validate, re-index |
Skill File Format
Each skill lives in its own folder containing a SKILL.md file with YAML frontmatter delimited by ---.
Folder structure rules
skills/
coding/ # group folder (has subfolders, no SKILL.md)
python/
fastapi/ # skill folder → contains SKILL.md
SKILL.md
pytest/
SKILL.md
rust/
tokio/
SKILL.md
- A folder is a skill if it contains
SKILL.md - A folder is a group if it has subfolders but no
SKILL.md - A folder can be dual (both group + skill) — has
SKILL.mdAND subfolders - Folders beyond
--max-depthare silently ignored - Empty folders (no
SKILL.md, no subfolders) are silently ignored - Use lowercase with hyphens for folder names:
web-scraping - All path lookups are case-insensitive —
"Coding/Python"and"coding/python"resolve to the same node - Case collisions are rejected at startup: having both
Coding/andcoding/folders will abort the server — use consistent casing
Frontmatter fields
| Field | Required | Type | Description |
|---|---|---|---|
name |
Yes | string | Unique identifier across the entire tree. Does not need to match folder name. |
tags |
No | list | Keywords for search: [python, api, web] |
aliases |
No | list | Alternative names an AI might search by: [fast api, fastapi framework] |
description |
No | string | One or two sentences explaining the skill. Indexed for search. |
depends_on |
No | list of paths | Prerequisites the AI should know first: [python/basics] |
related |
No | list of paths | Conceptually similar skills: [flask, starlette] |
followed_by |
No | list of paths | Natural next skills after mastering this one |
steps |
No | list of paths | Ordered sub-skill paths for multi-step workflows |
uses |
Auto | integer | Usage counter — auto-incremented by use() tool |
last_used |
Auto | string or null | ISO timestamp — auto-set by use() tool |
Example
---
name: fastapi
tags: [python, api, web]
aliases: [fast api, fastapi framework]
description: Python web framework for building APIs
depends_on: [python/basics]
related: [flask, starlette]
followed_by: [sqlalchemy, pytest]
uses: 0
last_used: null
steps: [setup/project-scaffold, coding/python/fastapi/routing]
---
After the closing ---, write standard Markdown body content. The server never modifies the body — only uses and last_used in the frontmatter are updated automatically.
Validation rules
On startup and reload() the server validates every skill:
SKILL.mdmust exist and have valid YAML frontmatternamefield is required and must be unique across the entire tree- Duplicate names cause an abort with per-skill error logging
- Folders with case-colliding paths (e.g.
Coding/andcoding/) cause an abort — use consistent casing - Folders beyond
--max-depthare silently ignored
Hierarchy guidelines
- Keep
--max-depthbetween 3 and 5 levels - Aim for 5–15 children per group node; split into sub-groups if exceeding 20
- Use dual nodes (folder with
SKILL.md+ subfolders) when a group has general content applying to all children - Prefer 3–8 tags per skill, lowercase, singular form
Project Structure
skills-mcp-server/
├── mcp_server.py # Root-level entry point
├── pyproject.toml # Project configuration
├── src/
│ ├── __init__.py # Package init
│ ├── __main__.py # Entry point
│ ├── main.py # CLI + server orchestration
│ ├── models.py # Data models
│ ├── frontmatter.py # YAML frontmatter parser
│ ├── discovery.py # Folder walker
│ ├── tree.py # In-memory skill tree
│ ├── index.py # Search index
│ ├── mcp_server.py # MCP tool definitions
│ ├── http_server.py # HTTP server for web UI
│ └── static/
│ └── index.html # Web UI (vanilla HTML/CSS/JS)
├── tests/
│ ├── test_discovery.py # Tests for discovery
│ ├── test_frontmatter.py # Tests for YAML parsing
│ └── test_tools.py # Tests for tree tools & search
├── sample_skills/ # Demo skills
├── HANDOFF.md # Session handoff notes
├── AGENTS.md # Agent conventions
└── IMPLEMENTATION_PLAN.md # Full implementation plan
Design Principles
- Hierarchy for humans, search for models — tree browsing and full-text search coexist
- Filesystem as source of truth — no database needed
- Minimal dependencies — only
mcpandpyyaml - Read-only web UI — no editing, no auth, no build step
- Self-improving index — usage tracking boosts popular/recent skills in search results
Tests
python -m pytest tests/ -v
Установка Hierarchical Skills For AI Server
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/Aunxfb/HierarchicalSkillsForAIFAQ
Hierarchical Skills For AI Server MCP бесплатный?
Да, Hierarchical Skills For AI Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Hierarchical Skills For AI Server?
Нет, Hierarchical Skills For AI Server работает без API-ключей и переменных окружения.
Hierarchical Skills For AI Server — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Hierarchical Skills For AI Server в Claude Desktop, Claude Code или Cursor?
Открой Hierarchical Skills For AI Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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