AgentsKit Registry

io.github.AgentsKit-io由 GitHub 帳號 AgentsKit-io 發布v1.0.0更新於 Oct 24, 2026

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

已驗證Streamable HTTP可網頁執行開發者工具AI 與機器學習

概覽

AI 產生的概覽

用來瀏覽 AgentsKit Registry 的遠端 MCP 伺服器:助理可以列出、搜尋與檢視開源 AI 代理,並取得其安裝指令。

可以做什麼
列出登錄表中的代理,可依類別篩選,並依自由文字、類別、標籤或可執行標記搜尋。取得單一代理的完整組合,包含中繼資料、環境設定、技能與原始碼檔案。取得所選代理的確切安裝指令與使用範例。
適用情境
適合讓助理從目錄中協助挑選現成的 AI 代理起點,並提供將原始碼複製到專案的指令。若已確定所需代理或未使用 AgentsKit,則幫助不大。
執行需求
透過 streamable HTTP 連線至 registry.agentskit.io 的遠端端點;未宣告驗證、環境變數或標頭。安裝所選代理需另外使用 AgentsKit CLI,並需要 Node.js。
安裝前請注意
登錄表仍為 beta,其範本屬於程式碼,上線前須依自己的模型供應商、工具、資料政策與風險狀況審查。安裝會將原始碼複製到專案,範例程式碼需要你自行提供如 OPENAI_API_KEY 的供應商金鑰。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 AgentsKit Registry,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.AgentsKit-io%2Fagentskit-registry/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "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.

來源:README.md,提交 b4cefef

工具

4

list_agents

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

輸入參數category

get_agent

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

輸入參數id必填

search_agents

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

輸入參數tagquerycategoryrunnable

get_install_command

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

輸入參數id必填

版本歷史

1
  1. v1.0.0最新Sep 16, 2026

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