A home for
your agent skills.
Serve Markdown instructions to your agents through the Model Context Protocol (MCP). Run your own server today, or explore the planned hosted account flow.
Available now: local, self-hosted and Google sign-in. Hosted MCP endpoints: coming soon.
Choose how
you run skillar.
Use the open-source tools on your own infrastructure, or explore the planned managed service. The choice is who runs the server, not whether your skills stay in Markdown.
| Setup | Local / self-hosted | Hosted account |
|---|---|---|
| Availability | Available in the repository | Google sign-in available; MCP endpoint coming soon |
| Endpoint | Your local or self-hosted URL | Account-scoped MCP endpoint planned |
| Operations | Your config, deployment and credentials | Managed provisioning planned |
| Pricing | Open-source software; your infrastructure costs | Not announced |
Local CLI and client integrations: MIT. Registry server and Cloudflare Worker: AGPL-3.0-only.
Remote self-hosting requires your own configuration and release validation. A skill read is not permission to execute its instructions.
Your account.
Your MCP endpoint.
The hosted flow: sign in with Google, connect an agent, then open the remote dashboard. Sign-in works today; the connection and dashboard steps are screen previews.
Signing in stores your Google ID, email, name, picture and sign-in times. No MCP endpoint or server is provisioned. Hosted pricing is not announced.
Sign in with Google
Google handles authentication. skillar stores your Google ID, email, name, picture and first and latest sign-in times, keeps your session in a signed, secure cookie, and retains no Google tokens.
Connect your agent
Use your account's MCP endpoint with client-specific configuration. The preview shows examples only: no endpoint is provisioned and no connection is made.
Review activity
Explore empty Sessions, Workspaces, Flow and Heatmap views in the planned remote dashboard. The local daemon does not upload captured activity; future hosted capture is not decided.
Your agent. Your workflow.
- Claude Code
- Codex
- Cursor
- OmO
- Gemini CLI
- Gajae Code
- OpenClaw
Local setup detects supported runtimes. Capture coverage and remote integration vary by client.
Write. Serve.
Put it to work.
Instructions stay in files you own. Agents find the right skill and read it when the task calls for it.
Start with a skill
A skill is a folder with a
SKILL.mdfile: a name, a description and the instructions your agent reads when a task calls for them.Give it a home
Index existing folders locally, or configure your own remote registry. Managed skill servers are coming soon.
Connect your agents
Search through
search_skills. Read the selected skill through MCP resources. Load the details on demand, not the whole library.
Just Markdown.
Actual know-how.
No new authoring language. A skill bundles instructions with the files that support them.
The local catalog indexes your folders in place. The registry exposes skills through MCP discovery and resource reads.
Read the registry docs---
name: skillar
description: Discover remote skills for a new task by searching its subject and intended outcome, then load only a relevant skill. Also discover native skill packs for requested combined workflows and create or update team skills/packs when requested. Searching does not activate a skill.
---
Use the Skillar MCP tools directly.Less setup.
More doing.
The local CLI can detect your runtimes, configure MCP, and install a background service. Preview its changes before you apply them.
Fresh install · macOS or Linux · Node.js 24.15+
Upgrading from gisool? Migrate firstnpm install -g skillarThen run skillar init. Installing over gisool collides on the gisool command, so migrate first.
# Preview without changing files
skillar init --dry-run
# Connect runtimes and install the background service
skillar init
# Inspect your skill activity
skillar openPrefer a foreground process? Instead of the service step above, run skillar init --no-service, then skillar serve.
Good questions.
What is an agent skill?
A folder containing a SKILL.md instruction file and optional supporting files. The name and description help an agent discover it; the body carries the actual instructions.
Can I use skillar today?
Yes. Install the local CLI with npm install -g skillar. Run skillar init --dry-run to preview setup changes. macOS or Linux and Node.js 24.15+ are required. If you are upgrading from gisool, read the migration guide first.
Is the hosted service live?
Partly. Google sign-in is live and stores a minimal profile: Google ID, email, name, picture and sign-in times. Managed MCP provisioning, the remote dashboard and hosted pricing are coming soon. The hosted accounts section describes the journey; nothing else on this site collects your email.
Does every MCP client work?
Skills require a host that can discover and read MCP resources. The repository includes runtime-specific integrations; compatibility and capture coverage vary. Check the protocol and compatibility guide for your client.
Where does my local data go?
The local daemon listens on loopback, uses a local bearer token, and stores indexed skills and captured session activity in local SQLite. It does not upload captured telemetry. Your connected agent and model provider handle data separately.
Can I host a registry for my team?
Yes. The repository includes a Node.js registry and a Cloudflare Worker for authenticated distribution from private R2 releases. You provide infrastructure and credentials. See the deployment guide.