AgentsKit Registry

io.github.AgentsKit-ioPublished by GitHub account AgentsKit-iov1.0.0Updated Oct 24, 2026

Discover open-source AI agents and get source-owned installation instructions through MCP.

VerifiedStreamable HTTPWeb executableDeveloper ToolsAI & ML

Overview

AI-generated overview

Remote MCP server for browsing the AgentsKit Registry: an assistant can list, search and inspect open-source AI agents and get their install commands.

What you can do
List agents in the registry, optionally filtered by category, and search them by free-text query, category, tag or runnable flag. Retrieve the full bundle for one agent, including metadata, environment settings, skill and source files. Get the exact install command and a usage snippet for a chosen agent.
When to use it
Useful when you want an assistant to help pick a ready-made AI agent starting point from a catalog and hand you the command to copy its source into your project. Less relevant if you already know which agent you want or do not use AgentsKit.
Requirements
A remote endpoint at registry.agentskit.io over streamable HTTP; no authentication, environment variables or headers are declared. Installing a chosen agent is done separately with the AgentsKit CLI, which needs Node.js.
Before you install
The registry is in beta and its templates are code you must review against your own provider, tools, data policy and risk profile before shipping. Installing an agent copies source into your project, and the sample code expects provider API keys such as OPENAI_API_KEY that you supply yourself.

Installation

In SourceWeft

  1. Open AgentsKit Registry in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.AgentsKit-io%2Fagentskit-registry/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "agentskit-registry": {
      "type": "http",
      "url": "https://registry.agentskit.io/api/mcp"
    }
  }
}

README

AgentsKit Registry

Profile: top-level-repository

[CI] [Agents] [License: MIT] [OpenSSF Best Practices]

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

[AgentsKit Registry deterministic-first discovery: 346 validated agents resolve exact questions locally and escalate semantic questions only when needed.]

Verified proof

  • Catalog counts come from public/r/index.json and ecosystem-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.

yaml
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

mermaid
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"]
bash
npx agentskit add research
ts
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:

bash
npm cinpm run check:no-legacy-chat-importsnpm run docs:bridge:confignpm run validatenpm run lintnpm testnpm run test:quickstartnpm run eval:run -- --ecosystem-doc-bridgenpm run buildnpm run docs:bridge:indexnpm run docs:bridge:gatenpm 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.

Source: README.md at commit b4cefef

Tools

4

list_agents

List all agents in the AgentsKit registry. Optionally filter by category.

Parameterscategory

get_agent

Get the full bundle for one agent: metadata, env, skill, and source files.

Parametersidrequired

search_agents

Search agents by free-text query, category, tag, or runnable flag.

Parameterstagquerycategoryrunnable

get_install_command

Get the exact install command and a usage snippet for an agent.

Parametersidrequired

Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

100% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts