About AgentsKit Registry
AgentsKit Registry is a catalog of reusable AI agent source for development teams. Its CLI copies readable TypeScript into a project, where teams can review and adapt it without adopting a registry runtime.
Key features
- 01Browse agents by ID, category, or capability
- 02Copy agent source with the CLI
- 03Typed source, tests, and usage guides
- 04Validate agent folders in GitHub Actions
- 05Discovery through JSON, llms.txt, and MCP
- 06Independent review summaries
Use cases
- 01Add a starter agent to a codebase
- 02Validate owned agent folders in CI
- 03Find an agent for a workflow
MCP support
The catalog is available through MCP, alongside JSON, llms.txt, and discovery artifacts. MCP provides a way for tools and LLMs to navigate the agent catalog.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://registry.agentskit.io/api/mcpclaude mcp add --transport http agentskit-io-agentskit-registry https://registry.agentskit.io/api/mcp{"mcpServers":{"agentskit-io-agentskit-registry":{"type":"http","url":"https://registry.agentskit.io/api/mcp"}}}Open in Cursor{"servers":{"agentskit-io-agentskit-registry":{"type":"http","url":"https://registry.agentskit.io/api/mcp"}}}Open in VS Code{"mcpServers":{"agentskit-io-agentskit-registry":{"type":"http","url":"https://registry.agentskit.io/api/mcp"}}}{"mcpServers":{"agentskit-io-agentskit-registry":{"serverUrl":"https://registry.agentskit.io/api/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
4| Parameter | Type | Required | Description |
|---|---|---|---|
| category | string | No |
Details
From the project READMEAgentsKit Registry
Profile: top-level-repository
Copy a production-minded AI agent into your project and own the source. AgentsKit Registry is a shadcn-style catalog of 346 validated agents built with AgentsKit. It adds no Registry runtime and no lock-in: the CLI copies readable TypeScript that your team can review and edit.
It is intended for teams that want a ready agent starting point without adopting a proprietary registry runtime.
Tags: agentskit · agent-registry · typescript · ai-agents · shadcn-style
Topics: ai-agents · registry · developer-experience
Browse the Registry · Start in five minutes · Contribute an agent · Security · Governance · Code of Conduct
Verified proof
- Catalog counts come from
public/r/index.jsonandecosystem-claims.json. - Clean-fixture install/run contract:
npm run test:quickstart(scripts/quickstart.test.mjs). - Structural validation and Doc Bridge gates:
npm run validate,npm run docs:bridge:gate. - Deterministic discovery build:
npm run discovery:build. - Credential-free catalog proof:
node examples/verify-readme.mjs.
Validate agents in GitHub Actions
Use the Registry contract as a CI gate for copy-owned agent folders in another repository. The action checks required source, test, metadata, and README files; metadata IDs and referenced files; and the Registry content policy. It does not send source code to an API or require credentials.
name: Validate agents
on:
pull_request:
push:
branches: [main]
jobs:
agentskit:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: AgentsKit-io/agentskit-registry@v1
with:
path: agents
The path input may point to one agent folder or to a directory whose immediate
children are agent folders.
Registry is beta. All 346 entries pass structural and repository tests; 333 also publish sanitized independent-review evidence. Templates remain code you must review against your provider, tools, data policy, and risk profile.
From catalog to code
flowchart LR
F["Find by ID, category, or capability"] --> A["npx agentskit add <id>"]
A --> C["Readable source copied locally"]
C --> R["Review and adapt"]
R --> S["Ship with your adapter and policy"]
npx agentskit add research
import { openai } from '@agentskit/adapters'
import { createResearchAgent } from './agents/research/agent'
const agent = createResearchAgent({
adapter: openai({
apiKey: process.env.OPENAI_API_KEY!,
model: 'gpt-4o',
}),
})
const result = await agent.run('What changed in the EU AI Act?')
console.log(result.content)
Swap the adapter, tools, memory, model, and policy through supported AgentsKit contracts. The copied factory stays ordinary application code.
What is actually here
- 346 validated, installable agents across 23 categories, from coding and security to legal, clinical, marketing, operations, support, and research.
- 333 independent-review summaries with scores, confidence, strengths, and reviewer notes; private raw reviewer output is never published.
- Typed source + focused tests + usage guide for every installable entry.
- Eval replay fixtures for repeatable behavioral checks without live keys.
- JSON,
llms.txt, MCP, and deterministic discovery artifacts for people, tools, and LLMs to navigate the same canonical catalog.
Claims are derived from public/r/index.json and the
generated ecosystem-claims.json, not hand-maintained
marketing copy.
Discovery without unnecessary backend calls
Exact agent IDs, titles, install commands, categories, capabilities, contribution links, and ecosystem navigation resolve from a local artifact pinned by content hash. Semantic requests such as “which agent fits my incident workflow?” escalate through AgentsKit Chat to the trusted cited backend only after a validated local miss.
See architecture and ownership for the full boundary.
Repository ownership
This repository owns catalog data and generated machine artifacts. The live
Fumadocs application and its AgentsChat presentation live in
AgentsKit-io/agentskit/apps/registry.
AgentsKit owns runtime primitives and the CLI; AgentsKit Chat owns the shared
answer protocol and renderer behavior. There is no second framework here.
Contributing
New agents and improvements are welcome. Follow CONTRIBUTING.md, use a neighboring validated agent as a reference, and run:
npm ci
npm run check:no-legacy-chat-imports
npm run docs:bridge:config
npm run validate
npm run lint
npm test
npm run test:quickstart
npm run eval:run -- --ecosystem-doc-bridge
npm run build
npm run docs:bridge:index
npm run docs:bridge:gate
npm run docs:bridge:conformance
Generated indexes, claims, deterministic artifacts, and Doc Bridge handoffs must remain fresh in the pull request.
Maturity
Registry is beta. All 346 entries pass structural and repository tests; 333 also publish sanitized independent-review evidence. Templates remain code you must review against your provider, tools, data policy, and risk profile.
AgentsKit ecosystem
- AgentsKit — build the agent runtime.
- Registry — start from owned, ready-made source.
- AgentsKit Chat — deliver one agent experience across Web, native, and terminal interfaces.
- Doc Bridge — turn documentation into executable agent handoffs. Optional companion for repositories that install agents: how it fits.
- Code Review — run deep, low-noise review with the model already in use.
- Harness — the keep-pushing delivery loop for your SDLC.
Compatibility and license
Registry source targets the package ranges declared by each meta.json; the
repository CI currently runs on Node.js 22. Review an agent's generated bundle
before upgrading its dependencies. Licensed under MIT.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.