- Add Claude Code Plugin: plugin.json, .mcp.json, 3 slash commands, skill-builder agent skill - Add GitHub Action: composite action.yml with 6 inputs/2 outputs, comprehensive README - Add Smithery: publishing guide with namespace yusufkaraaslan/skill-seekers created - Add render-mcp.yaml for MCP server deployment on Render - Fix Dockerfile.mcp: --transport flag (nonexistent) → --http, add dynamic PORT support - Update AGENTS.md to v3.3.0 with corrected test count and expanded CI section - Allow distribution/claude-plugin/.mcp.json in .gitignore
Skill Seekers — Smithery MCP Registry
Publishing guide for the Skill Seekers MCP server on Smithery.
Status
- Namespace created:
yusufkaraaslan - Server created:
yusufkaraaslan/skill-seekers - Server page: https://smithery.ai/servers/yusufkaraaslan/skill-seekers
- Release status: Needs re-publish (initial release failed — Smithery couldn't scan GitHub URL as MCP endpoint)
Publishing
Smithery requires a live, scannable MCP HTTP endpoint for URL-based publishing. Two options:
Option A: Publish via Web UI (Recommended)
- Go to https://smithery.ai/servers/yusufkaraaslan/skill-seekers/releases
- The server already exists — create a new release
- For the "Local" tab: follow the prompts to publish as a stdio server
- For the "URL" tab: provide a hosted HTTP endpoint URL
Option B: Deploy HTTP endpoint first, then publish via CLI
- Deploy the MCP server on Render/Railway/Fly.io:
# Using existing Dockerfile.mcp docker build -f Dockerfile.mcp -t skill-seekers-mcp . # Deploy to your hosting provider - Publish the live URL:
npx @smithery/cli@latest auth login npx @smithery/cli@latest mcp publish "https://your-deployed-url/mcp" \ -n yusufkaraaslan/skill-seekers
CLI Authentication (already done)
# Install via npx (no global install needed)
npx @smithery/cli@latest auth login
npx @smithery/cli@latest namespace show # Should show: yusufkaraaslan
After Publishing
Update the server page with metadata:
Display name: Skill Seekers — AI Skill & RAG Toolkit
Description:
Transform 17 source types into AI-ready skills and RAG knowledge. Ingest documentation sites, GitHub repos, PDFs, Jupyter notebooks, videos, Confluence, Notion, Slack/Discord exports, and more. Package for 16+ LLM platforms including Claude, GPT, Gemini, LangChain, LlamaIndex, and vector databases.
Tags: ai, rag, documentation, skills, preprocessing, mcp, knowledge-base, vector-database
User Installation
Once published, users can add the server to their MCP client:
# Via Smithery CLI (adds to Claude Desktop, Cursor, etc.)
smithery mcp add yusufkaraaslan/skill-seekers --client claude
# Or configure manually — users need skill-seekers installed:
pip install skill-seekers[mcp]
Manual MCP Configuration
For clients that use JSON config (Claude Desktop, Claude Code, Cursor):
{
"mcpServers": {
"skill-seekers": {
"command": "python",
"args": ["-m", "skill_seekers.mcp.server_fastmcp"]
}
}
}
Available Tools (35)
| Category | Tools | Description |
|---|---|---|
| Config | 3 | Generate, list, validate scraping configs |
| Sync | 1 | Sync config URLs against live docs |
| Scraping | 11 | Scrape docs, GitHub, PDF, video, codebase, generic (10 types) |
| Packaging | 4 | Package, upload, enhance, install skills |
| Splitting | 2 | Split large configs, generate routers |
| Sources | 5 | Fetch, submit, manage config sources |
| Vector DB | 4 | Export to Weaviate, Chroma, FAISS, Qdrant |
| Workflows | 5 | List, get, create, update, delete workflows |
Maintenance
- Update description/tags on major releases
- No code changes needed — users always get the latest via
pip install
Notes
- Smithery CLI v4.7.0 removed the
--transport stdioflag from the docs - The CLI
publishcommand only supports URL-based (external) publishing - For local/stdio servers, use the web UI at smithery.ai/servers/new
- The namespace and server entity are already created; only the release needs to succeed