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PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

JobMojito

作者:JobMojito版本 1.5.0i★ –i在云端运行
注册名称com.jobmojito/jobmojito

安装

概览

作者提供的说明(英文原文)

Run AI interviews, simulated personas and coaching sessions on JobMojito.

PopNx MCP 的三大支柱

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。

它能帮你做什么

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。

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

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:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://mcp.jobmojito.com/mcp

在终端中运行这条命令

claude mcp add --transport http jobmojito https://mcp.jobmojito.com/mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "jobmojito": {
      "url": "https://mcp.jobmojito.com/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。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "jobmojito": {
      "type": "http",
      "url": "https://mcp.jobmojito.com/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:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://mcp.jobmojito.com/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。

它能做什么

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。

基础检查i

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

  • ✓ 通过

    作者与仓库一致

    注册名称已通过域名 jobmojito.com 验证(注册中心会核实域名所有权)

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • ✓ 通过

    端点有响应

    在 675 毫秒内响应(HTTP 200)

  • – 不适用

    使用 OAuth 登录

    无需登录

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32583 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32583 个服务器的 90% 更新
  • 基础检查结果等于或优于此分类中其他 32583 个服务器的 100%

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。

常见问题

JobMojito 安全吗?

它在 2 项适用的基础检查中通过了 2 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。

它需要哪些密钥或代码?

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。

它在我的电脑上运行还是在云端?

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。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.5.0)于3天前进入注册中心。

哪些应用可以使用它?

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。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, sync. labs

替代选择

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

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
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sync. labs

作者:synchronicity-labs

Lipsync videos, dub them into other languages, make talking videos and open sync. Studio.

电脑或云端今天更新
安装

作者的 README

打开 README

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。

JobMojito MCP Server

Welcome

JobMojito runs AI-led conversational sessions in three shapes. The difference between them matters, because one tool builds two of them:

  • Interviews — a scored Q&A for hiring. Generate the questions from a job description or supply your own; run them with a voice-only interviewer, a live video avatar or a pre-recorded one, in 30+ languages, with a fully branded candidate experience.
  • Simulated personas — instead of a question list, the avatar plays a defined character in free-form conversation — a sceptical buyer, an angry customer, a difficult stakeholder — and the person is scored on how they handle it. Same invitation, billing and result flow as an interview, so these land in the recruiter's result list alongside everything else.
  • Coaching — the same persona engine pointed at practice rather than assessment. Learners start sessions themselves from a browsable catalogue, pay per second from their own coaching minutes, and their results stay private from recruiters. Organise it with directories, tag filters and Markdown pages.

The one trap. create_persona builds both the second and the third product,

selected by its portal argument — and it defaults to `coaching`. For

anything used to assess or screen, pass portal="interview" explicitly, or you

silently get the wrong product: billed to the wrong credits and invisible to the

recruiter.

Across all three: register candidates in bulk and give each a personal link, upload documents to a knowledge base the AI draws on, read back transcripts, structured analysis and shareable HTML or PDF reports, and manage workspaces, credits and analytics across merchants and sub-merchants.

Everything the platform produces is decision support for a qualified human reviewer — never the hiring decision itself, and candidates are told AI is part of the process.

Around the product: the admin console at app.jobmojito.com, developer/API docs at developer.jobmojito.com, the help center at help.jobmojito.com, and the hosted MCP endpoint this repo powers at https://mcp.jobmojito.com/mcp.

This repository is the MCP server that puts all of that into AI assistants like Claude and ChatGPT.


An MCP server for the JobMojito API, built with FastMCP and designed to deploy on Prefect Horizon (the MCP platform from the FastMCP team — app.prefect.cloud → Horizon).

It exposes:

  • 39 API tools auto-generated from JobMojito's live OpenAPI spec (interviews, simulated personas and the coaching catalogue, candidates and results, knowledge base, merchant lists/analytics, custom reports, portal configuration). All endpoints — including the GET lists — are surfaced as tools with clean, curated names, each with a title and read-only/destructive annotations.
  • 2 documentation tools (search_documentation, get_documentation) that read the developer docs and help center live — docs stay single-source on their existing platforms; nothing is copied into this repo.
  • Supabase OAuth so end users can log in directly from Claude, ChatGPT, etc. The signed-in user's Supabase JWT is forwarded to the JobMojito API on every call.

How it fits together

MCP client (Claude / ChatGPT)

│ OAuth login (Supabase OAuth Server, DCR) ▼ JobMojito MCP server (this repo, on Horizon) │ forwards the user's Supabase JWT ▼ JobMojito API (https://cool.jobmojito.com/functions/v1)

ConcernApproach
API → toolsFastMCP.from_openapi(...), all routes mapped to Tools, curated names via injected operationIds
Spec freshnessFetched live at startup; a runtime cache + committed snapshot are fallbacks
AuthSupabaseProvider (Remote OAuth); per-request JWT forwarding to the upstream API
DocsBuilt-in tools reading developer.jobmojito.com/llms.txt + .md and the help.jobmojito.com (Featurebase) help center
Files
FilePurpose
server.pyEntry point — builds and exposes mcp (point Horizon at server.py:mcp)
config.pyEnvironment-driven settings
openapi_loader.pyLive fetch + cache/snapshot fallback + operationId injection
naming.pyCurated tool names, titles, hints and annotations per endpoint
upstream.pyhttpx client that forwards the user's Supabase JWT to the API
middleware.pyCall logging, upstream-error rewriting, result-size guard, annotation backfill
merchants.pyMerchant picker (MCP App UI) + list_my_merchants text fallback
docs_tools.pysearch_documentation / get_documentation
featurebase.pyFeaturebase REST client (help-center articles)
mintlify.pyMintlify developer-docs MCP proxy + client-credentials auth
tests/test_smoke.py (inventory, schema relaxation, docs) + test_listing_readiness.py (directory contract)
docs/Developer docs: architecture, development, deployment
scripts/update_snapshot.pyRefresh the committed fallback spec
scripts/try_docs.pyLocal smoke test for the documentation tools
data/openapi.snapshot.jsonOffline fallback spec (regenerate from your machine)
lazy_auth.pyUnauthenticated capability discovery + scope= on the 401 challenge
wellknown.py/healthz, OpenAI domain challenge, Smithery server card
server.jsonOfficial MCP Registry entry
.github/workflows/publish-registry.ymlPublishes server.json to the MCP Registry when a push to main changes server.py:SERVER_VERSION (or via manual dispatch)

Local development & testing (macOS)

# 1. Set up a virtualenv and install deps

python3 -m venv .venv && source .venv/bin/activate pip install -r requirements.txt

2. Configure secrets in .env (auto-loaded; gitignored)

cp .env.example .env # then fill in your keys/credentials

3. Static check — see exactly what Horizon will deploy

fastmcp inspect server.py:mcp

4. Run the unit tests (offline; uses the snapshot fallback)

ENABLE_AUTH=false pytest -q --asyncio-mode=auto

5. Smoke-test the docs tools live (Featurebase + Mintlify federation)

ENABLE_AUTH=false python scripts/try_docs.py "how do I create an interview"

6. Run the server and connect a client

ENABLE_AUTH=false python server.py # → http://localhost:8000/mcp

then, in another terminal, open the MCP Inspector:

npx @modelcontextprotocol/inspector

transport: "Streamable HTTP", URL: http://localhost:8000/mcp

Testing notes:

  • Docs tools (search_documentation, and the mounted Mintlify search_*_developer_* / query_docs_filesystem_*) work with ENABLE_AUTH=false — no Supabase login needed. scripts/try_docs.py is the fastest check.
  • API tools (create_interview, list_candidates, …) call the real JobMojito API and need a Supabase user token. For local testing, set JOBMOJITO_DEV_BEARER_TOKEN in .env to a valid Supabase access token; it's forwarded when ENABLE_AUTH=false. (Never set this in production — there the token comes from the user's OAuth session.)
  • Full OAuth locally is rarely needed; if you want it, run with ENABLE_AUTH=true, set BASE_URL=http://localhost:8000, and connect a client that supports OAuth (it will bounce you through Supabase).

Refresh the fallback snapshot from a network that can reach the API:

python scripts/update_snapshot.py (the committed snapshot in this repo is a

thin structural fallback; this replaces it with the full live spec).


Supabase OAuth setup

This server uses Supabase's OAuth Server feature (which supports Dynamic Client Registration, so MCP clients self-register). The MCP server is the OAuth resource server — it validates tokens; Supabase issues them.

Project: https://momsbvnltsydezmoesqt.supabase.co SupabaseProvider derives every endpoint from this project URL:

EndpointURL
Authorize…/auth/v1/oauth/authorize
Token…/auth/v1/oauth/token
JWKS…/auth/v1/.well-known/jwks.json
OIDC discovery…/auth/v1/.well-known/openid-configuration

Steps:

  1. Supabase Dashboard → Authentication → OAuth Server
  • Enable the OAuth Server and Allow Dynamic OAuth Apps
  • Site URL: https://app.jobmojito.com
  • Authorization Path: /oauth/consent
  1. Env: SUPABASE_PROJECT_URL=https://momsbvnltsydezmoesqt.supabase.co, BASE_URL=https://mcp.jobmojito.com (public base, no /mcp), SUPABASE_JWT_ALGORITHM=ES256 (switch to RS256 if your JWKS shows RSA keys).
  2. If the JobMojito Edge Functions require an apikey header, set SUPABASE_ANON_KEY.

Consent is handled by Supabase / your app, not this server. Because the Site URL is app.jobmojito.com, Supabase serves the approve/deny screen at https://app.jobmojito.com/oauth/consent, where the user already has a Supabase session. This MCP server is only the OAuth resource server — it does not serve a consent page. SITE_URL and OAUTH_CONSENT_PATH are informational and should match your Supabase OAuth Server settings.

Token note: SupabaseProvider cannot validate token *audience* (Supabase Auth

doesn't implement RFC 8707 resource indicators yet). This is expected and

logged at startup.


Authentication model

**Every tool *call* requires the user to be signed in via Supabase OAuth** — including search_documentation and get_documentation. Keep ENABLE_AUTH=true; the signed-in user's token is forwarded to the JobMojito API so calls respect that user's permissions.

The one deliberate exception is capability discovery: with ENABLE_LAZY_AUTH (default true), initialize, ping and the */list methods answer without a token so directory crawlers can render the tool list. No data is reachable that way — every tools/call, resource read and prompt still needs a verified JWT.

Deploy to Prefect Horizon

  1. Push this repo to GitHub.
  2. At horizon.prefect.io, sign in with GitHub and select this repo.
  3. Configure:
  • Entrypoint: server.py:mcp
  • Dependencies: auto-detected from requirements.txt
  • Horizon Authentication: off — this server provides its own Supabase OAuth, so let it be the auth layer.
  1. Set environment variables / secrets:
  • ENABLE_AUTH=true
  • BASE_URL=https://mcp.jobmojito.com — critical. This must be the server's public base URL, with no `/mcp` and no trailing slash. It's what SupabaseProvider advertises as the OAuth resource; if it's left at the http://localhost:8000 default, clients get 401 invalid_token. The startup log prints base_url=… and warns if it's localhost.
  • SUPABASE_PROJECT_URL=https://momsbvnltsydezmoesqt.supabase.co
  • SUPABASE_ANON_KEY if the Edge Functions need the apikey header.
  • FEATUREBASE_API_KEY for help-center docs.
  1. Deploy. Your MCP endpoint is https://mcp.jobmojito.com/mcp. Horizon redeploys on every push to main.
Testing the login

A 401 on initialize is the normal first step of MCP OAuth — the client is meant to read the discovery metadata and run the Supabase login. Horizon's Inspector / ChatMCP do not perform that login, so they'll show a bare 401. Test by adding https://mcp.jobmojito.com/mcp as a custom connector in Claude.ai, which runs the full OAuth flow and prompts the Supabase login.

Make sure the Supabase side is configured (or the flow 401s regardless): OAuth Server enabled + Dynamic Client Registration on; Site URL https://app.jobmojito.com

  • Authorization Path `/

只显示了开头部分;其余内容请在仓库中阅读

问 PopNx