Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Search jobs on verified employer job boards. Every link is the employer's own posting.
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://openings.avagama.co/mcp터미널에서 이 명령어를 실행하세요
claude mcp add --transport http openings https://openings.avagama.co/mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"openings": {
"url": "https://openings.avagama.co/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": {
"openings": {
"type": "http",
"url": "https://openings.avagama.co/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://openings.avagama.co/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 7일 점검
레지스트리 이름이 도메인 avagama.co 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(0.1.65)은 24일 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.
A free, candidate-safe job search for AI agents.
Openings indexes public company job boards into a private index on your machine and exposes it to any MCP client. Your agent can find roles that fit a resume, explain the fit with evidence, and propose truthful resume improvements. Installed this way there are no accounts and no API keys; there are never model calls and never a way to submit an application.
Two ways to run it, with different data rules:
| On your machine (this package) | Hosted connector at openings.avagama.co/mcp | |
|---|---|---|
| Sign-in | None | Email code, so an account exists |
| Job index | Built and stored on your machine | Ours, shared |
| Resume | Parsed in memory for one request, never written to disk | Sent to our server, processed in memory for that request, then discarded |
| What we receive | Crawl reports, plus anonymous usage events unless you turn them off | The same usage record, keyed to your account |
Both are covered in Sharing crawls and usage and on the privacy page.
Install Bun 1.3 or newer, then the package with whichever package manager you use:
bun add --global openings
npm install --global openings
yarn global add openings
Bun must be on your PATH either way; it is the runtime the server runs on.
Add the server to your MCP client:
{
"mcpServers": { "openings": { "command": "openings-mcp", "args": [] } } }
Then ask your agent something like:
Show me what Openings covers in India. If that looks useful, use my resume to find backend roles, including good jobs whose titles I would not have searched for. Rank by evidence and explain every gap.
On first use the agent downloads the shared index of every verified source in one call, reports real coverage, and only then asks for a resume; only missing or stale sources are crawled, in batches of 25. Results come back in three buckets: direct title matches, hidden roles found through grounded title families, and stretch roles, each with separate evidence and keyword scores. The index lives under ~/.openings.
The job-seeker quickstart has sample prompts, an example conversation, privacy details, and common errors.
| Tool | What it does |
|---|---|
prepare_job_search | Builds or refreshes the index for your countries and reports coverage. Uses the network, never touches a resume. |
get_job_coverage | Reports current coverage with no network access. |
recommend_jobs | Ranks jobs against a resume and explicit intent. Returns direct, hidden, and stretch results with evidence. Performs at most one scoped refresh; refresh.policy: "never" guarantees no crawl. |
analyze_job_fit | Explains one job against verbatim resume evidence: supported, transferable, unsupported, and screening risks. |
optimize_resume | Proposes grounded suggestions, an additive diff, or revised Markdown. Never invents experience. |
search_jobs | Resume-free keyword, location, country, remote, and stated-experience search, newest first. country takes a two-letter code such as IN. Optional experienceYears compares stated min/max ranges, excluding unknowns unless includeUnknownExperience: true. Results include pagination.total and pagination.nextOffset; request the next page with that offset, unchanged filters, and maxAgeDays set to the returned window.daysUsed. Restart pagination after index refresh; this is not a frozen snapshot cursor. Without maxAgeDays, search widens through 7/14/30/all days until at least five results exist. |
get_job | Returns one job with its full description. |
There is deliberately no form-fill, apply, or submit tool. The only thing Openings writes is your own job index.
bun install
bun run src/mcp.ts # stdio MCP server bun run src/cli.ts crawl --country IN # build the index bun run src/cli.ts search "platform engineer" --remote bun run src/cli.ts get greenhouse:anthropic:12345
CLI commands return JSON. Search refreshes a missing or stale index automatically; pass --offline to guarantee no network request. The source entrypoint stores its index under .openings in the working directory unless OPENINGS_DATA_DIR is set. The included .mcp.json is picked up when this repository is installed as a Codex plugin.
Discovery campaigns, source verification, corpus expansion, coverage reports, and lock recovery are documented in the maintainer guide.
Append a candidate to data/source-candidates.json and run verification. Never edit the generated catalog in data/companies.json by hand.
{
"companyName": "Example", "companyDomain": "example.com", "sourceUrl": "https://job-boards.greenhouse.io/example", "cohorts": ["IN"], "discoveredFrom": { "channel": "community", "reference": "issue-123" } }
bun run src/cli.ts sources verify data/source-candidates.json
The verifier resolves the canonical board endpoint, validates its payload, applies the provider's identity check, and regenerates the catalog atomically. Rejected candidates are reported with a machine-readable reason. Boards discovered without a known company website can enter as *board-verified* sources instead, admitted on the provider's own identity and marked provider_board in the catalog so tools and pages can label them; see the maintainer guide. cohorts records why a source was selected for a country campaign; eligibility is always decided per job. An optional slug keeps existing job IDs stable when it differs from the first label of the company domain.
The packaged server reports each source you crawl to the shared Openings aggregator at openings.avagama.co, which merges reports from every install and publishes the result. New installs download the published index for their countries on first setup instead of crawling every source. Only public job data is sent in crawl reports, never resume content.
The server also sends anonymous usage events so we can see what people search for and improve coverage. Each install gets a random ID on first run, stored in the data directory. An event records the tool that ran, the countries, the intent fields you passed (roles, seniority, skills, remote, query text), the IDs of jobs you opened, and the skill and title values the parser extracted from a resume. It never includes the resume text, the quoted evidence, your name, or contact details, and no IP address is stored with it. Set OPENINGS_USAGE=off to stop usage events while keeping the shared index, or set OPENINGS_AGGREGATOR_URL to an empty string to keep everything local. The source entrypoint reports only when the aggregator variable is set.
On startup the server makes one request to the npm registry to learn the latest version. If yours is older, every tool result carries an updateAvailable note so your AI app can tell you to run bun add --global openings. Nothing on your machine is changed automatically. Set OPENINGS_UPDATE_CHECK=off to skip the check.
Job data comes straight from public ATS endpoints and is stored only on your machine. Your MCP client reads the resume file and passes its content to a tool; Openings never sees the path, and it never writes the resume to disk, logs it, or sends it anywhere.
One thing derived from a resume does leave your machine while usage reporting is on, which is the default: the skill and title words the parser extracted, in the anonymous event described in Sharing crawls and usage. Never the resume text, the quoted evidence, your name, or your contact details. OPENINGS_USAGE=off stops it, and an empty OPENINGS_AGGREGATOR_URL keeps everything local.
Every proposed change stays subject to your review.
bun test
bun run typecheck bun run test:live # one real board per provider, needs internet
MIT