Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Search jobs on verified employer job boards. Every link is the employer's own posting.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
适用于网页版、桌面版和手机版 Claude:
https://openings.avagama.co/mcp在终端中运行这条命令
claude mcp add --transport http openings https://openings.avagama.co/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"openings": {
"url": "https://openings.avagama.co/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"openings": {
"type": "http",
"url": "https://openings.avagama.co/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
ChatGPT 只能连接互联网上的服务器:
https://openings.avagama.co/mcp菜单名称可能因套餐和版本不同而略有差异。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过域名 avagama.co 验证(注册中心会核实域名所有权)
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(0.1.65)于25天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Context7, Codebase Memory, Exa
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间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.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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