Context7
Up-to-date docs for AI agents
作者による説明(英語の原文)
Search jobs on verified employer job boards. Every link is the employer's own posting.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
ウェブ、デスクトップ、モバイルのClaudeで使えます:
https://openings.avagama.co/mcpターミナルでこれを実行します
claude mcp add --transport http openings https://openings.avagama.co/mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"openings": {
"url": "https://openings.avagama.co/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"openings": {
"type": "http",
"url": "https://openings.avagama.co/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
ChatGPTがつなげるのは、インターネット上のサーバーだけです:
https://openings.avagama.co/mcpメニューの名前は、プランや時期によって少し違うことがあります。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
このサーバーのツール一覧はまだ読み取っていません。エンドポイントは順番にチェックしています。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
レジストリ名はドメイン avagama.co で確認済みです(レジストリがドメインの所有を確認しています)
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントをチェックするときにツール一覧を読み取ります
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
作者のクラウドで動きます。インストール不要でインターネット経由でつながりますが、送った内容は作者のサーバーを通ります。
GitHubリポジトリの最終更新は–、最新バージョン(0.1.65)がレジストリに届いたのは24 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。
同じカテゴリには:Context7, Codebase Memory, Exa
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
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