Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Connect agents to 6DuckLearn memory, approvals, and runtime control.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:
https://6ducklearn.com/mcp터미널에서 이 명령어를 실행하세요
claude mcp add --transport http 6ducklearn https://6ducklearn.com/mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"6ducklearn": {
"url": "https://6ducklearn.com/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"6ducklearn": {
"type": "http",
"url": "https://6ducklearn.com/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:
https://6ducklearn.com/mcp메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
아직 이 서버의 도구 목록을 읽지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 도메인 6ducklearn.com 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.1.1)은 5개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Official public setup docs, registry metadata, and local connector package for 6DuckLearn integrations.
This repository contains two separate integrations: Hosted MCP lets Codex use 6DuckLearn tools; the AI Runtime Connector lets Agent Console send work to Codex, Hermes, or OpenClaw.
Use 6ducklearn as the local client key in Codex or Claude Code. The official MCP Registry name is com.6ducklearn/mcp, and the hosted endpoint is:
https://6ducklearn.com/mcp
This repository is intentionally hosted-first. It does not contain the private 6DuckLearn SaaS backend, Supabase edge functions, service-role database access, billing logic, user memory store, or production deployment scripts.
From GitHub:
npx github:kit18/6ducklearn-mcp setup-codex
This configures the hosted 6DuckLearn MCP server in local Codex, adds the hosted OAuth compatibility header, and starts the OAuth login flow. If a matching, authenticated 6ducklearn hosted entry already exists, the setup command keeps it in place and does not reopen OAuth. A different local or stdio entry is replaced, while a matching but signed-out entry resumes OAuth, so repeated setup stays deterministic without creating duplicates.
Manual fallback:
Do not use codex mcp add for this fallback: current Codex versions can start OAuth immediately from that command, before explicit scopes are supplied. Inspect the entry first with codex mcp get 6ducklearn --json:
~/.codex/config.toml.http_headers table.codex mcp remove 6ducklearn, then add the full block.[mcp_servers.6ducklearn]
url = "https://6ducklearn.com/mcp"
[mcp_servers.6ducklearn.http_headers] User-Agent = "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125 Safari/537.36"
Start only the explicitly scoped login:
codex mcp login 6ducklearn --scopes mcp:read,mcp:write,approval:request
claude mcp add --transport http 6ducklearn https://6ducklearn.com/mcp
Then open the MCP tool picker in Claude Code and authorize 6DuckLearn when prompted.
The npm packages @6ducklearn/mcp and @6ducklearn/connector are not published yet. Until npm publication is available, use the GitHub npx command above for copy/paste setup.
6ducklearncom.6ducklearn/mcp6DuckLearn MCPhttps://6ducklearn.com/mcphttps://6ducklearn.com/.well-known/oauth-authorization-serverhttps://6ducklearn.com/.well-known/oauth-protected-resource/mcpThe public Codex helper requests only mcp:read, mcp:write, and approval:request. Control-plane access and local-runtime authorization use separate, explicitly named flows; the hosted-MCP setup never requests approval:decide. A protected write is submitted to 6DuckLearn Inbox with a server-issued approval ID. The human decides there, then Codex calls resume_approved_write with only that ID to execute the locked request once.
6DuckLearn MCP gives connected agents account-authorized workflows for research, organization, reminders, portfolio review, knowledge retrieval, canvas creation, and Skill Builder discovery. Finance research includes bounded stock-research bundles and issuer-grounded Hong Kong credit-card evaluation when those capabilities are enabled for the connected account.
For the full public catalog, see MCP tool use cases. The catalog describes each tool by practical use case and example prompt without exposing private schemas or backend implementation details.
Finance-related capabilities are for research, organization, summaries, alerts, and user-authorized workflows. 6DuckLearn MCP is not an order-routing service or source of investment recommendations.
Ask for a stock bundle when you want the available value, timing, event, risk, saved-research, and portfolio inputs in one read-only response:
Build a 90-day cached research bundle for 0700.HK. Include upcoming dates for the next 90 days, identify stale or missing evidence, and do not give trading instructions.
For Hong Kong credit cards, separate evidence lookup from evaluation:
First show the published dining-card evidence and freshness. Then evaluate annual net value for HKD 8,000 of monthly dining spend, excluding welcome offers and disclosing every missing or unverified field.
query_credit_card_catalog never ranks cards. recommend_credit_cards evaluates only the currently published, source-linked catalog and may return a limited, stale, or insufficient-data status instead of a winner. Missing normalized fields remain disclosures; they are not permission to invent reward rates, eligibility, fees, or ranking evidence.
The connector is for users who want a local runtime bridge between 6DuckLearn and AI runtimes such as Codex, OpenClaw, or Hermes. The preferred setup path is OAuth from the 6DuckLearn web app.
npm install
npm run build SIXDUCK_PUBLIC_BASE_URL=https://6ducklearn.com node packages/connector/dist/index.js login
After login, keep the connector process running when using a local runtime:
SIXDUCK_RUNTIME_TYPE=codex \
SIXDUCK_CODEX_CWD=/absolute/path/to/your/workspace \ SIXDUCK_CODEX_QUIET_PROFILE=true \ node packages/connector/dist/index.js
Most users should start from the hosted 6DuckLearn setup page rather than cloning this repository directly.
The official registry manifest lives in server.json. It is a hosted-only listing because the canonical 6DuckLearn MCP server runs at https://6ducklearn.com/mcp; the local connector is a runtime bridge, not a standalone stdio MCP server package.
Before publishing, validate the manifest and hosted endpoint:
npm run validate:registry
npm run smoke:hosted
Publish with domain-based authentication so the registry name can stay under the 6DuckLearn domain namespace:
# After generating the proof key and serving /.well-known/mcp-registry-auth:
mcp-publisher login http --domain 6ducklearn.com --algorithm ecdsap384 --private-key "$PRIVATE_KEY" mcp-publisher publish curl "https://registry.modelcontextprotocol.io/v0.1/servers?search=com.6ducklearn/mcp"
The required HTTP proof must be served from https://6ducklearn.com/.well-known/mcp-registry-auth. After the official MCP Registry lists com.6ducklearn/mcp, request GitHub MCP Registry inclusion by emailing partnerships@github.com with the registry name, official registry URL, GitHub repository, website, hosted endpoint, and validation evidence. GitHub's MCP Registry is a separate curated surface, so listing there currently requires GitHub review rather than relying on automatic community registry sync.
npm install
npm run validate
Validation runs TypeScript build, connector tests, package dry-run, MCP Registry manifest checks, hosted MCP smoke checks, and a public-release secret scan.
Report security issues privately. See SECURITY.md.
Code is licensed under Apache-2.0. Documentation examples are licensed under CC BY 4.0. See TRADEMARK.md for 6DuckLearn brand usage.