AgentsKit Registry

io.github.AgentsKit-io由 GitHub 账号 AgentsKit-io 发布v1.0.0更新于 Oct 24, 2026

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

已验证Streamable HTTP可网页运行开发者工具AI 与机器学习

概览

AI 生成的概览

用于浏览 AgentsKit Registry 的远程 MCP 服务器:助手可以列出、搜索和查看开源 AI 智能体,并获取其安装命令。

可以做什么
列出注册表中的智能体,可按类别筛选,并按自由文本、类别、标签或可运行标记搜索。获取单个智能体的完整包,包括元数据、环境配置、技能和源文件。获取所选智能体的确切安装命令和使用片段。
适用场景
适合让助手从目录中帮忙挑选现成的 AI 智能体起点,并给出把源码复制到项目中的命令。若已确定所需智能体或不使用 AgentsKit,则意义不大。
运行要求
通过 streamable HTTP 连接 registry.agentskit.io 的远程端点;未声明认证、环境变量或请求头。安装所选智能体需另行使用 AgentsKit CLI,并需要 Node.js。
安装前请注意
注册表处于 beta 阶段,其模板属于代码,上线前须结合自己的模型提供商、工具、数据政策和风险状况进行审查。安装会把源码复制到项目中,示例代码需要你自行提供如 OPENAI_API_KEY 的提供商密钥。

安装

在 SourceWeft 中

  1. 打开 控制台中的 AgentsKit Registry,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.AgentsKit-io%2Fagentskit-registry/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "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.

来源:README.md,提交 b4cefef

工具

4

list_agents

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

输入参数category

get_agent

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

输入参数id必填

search_agents

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

输入参数tagquerycategoryrunnable

get_install_command

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

输入参数id必填

版本历史

1
  1. v1.0.0最新Sep 16, 2026

评分

已满足适用检查项的 100%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

  • 近 30 天内可连通必需25 分
  • 已声明认证方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分