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Start a free trial on cloud.anythingmcp.com, add the Lever in one click, then point your AI client (Claude, ChatGPT, Copilot or Cursor) at the generated MCP endpoint. No Docker, no git clone, zero engineering experience required.
Summary
Manage Lever ATS (candidates, opportunities, postings, stages, feedback) from any AI agent. 10 tools, basic-auth.
Frag einfach
Beispiel-Prompts für Lever
Klick auf einen Prompt, um ihn zu kopieren. In Claude, ChatGPT, Cursor, Gemini, Copilot oder OpenClaw einfügen — und gegen diesen Konnektor laufen lassen.
Claude ist KI und kann Fehler machen. Bitte Antworten gegenprüfen.
💡 Keine Installation? Nutze cloud.anythingmcp.com direkt. Einloggen, Connectors → Lever klicken, Zugangsdaten einfügen, MCP-API-Key erzeugen — fertig. Kein Docker, kein
git clone, kein lokaler Server.
Lever + Gemini
Manage Lever ATS (candidates, opportunities, postings, stages, feedback) from any AI agent. 10 tools, basic-auth.
Voraussetzungen
Die vollständige Setup-Anleitung ist in den Connector eingebaut (im Store sichtbar, wenn du den Connector auswählst). Benötigte Umgebungsvariablen für diesen Connector:
LEVER_API_KEY
Schritt 1 — Zugangsdaten holen
This connector wraps the Lever Hire API v1 (api.lever.co/v1).
Setup:
- In Lever → Settings → Integrations and API → API Credentials → Generate new key.
- Set
LEVER_API_KEY. - Sandbox: use
https://api.sandbox.lever.co/v1instead during testing.
Authentication: HTTP Basic — API key as username, empty password.
Opportunity vs Candidate: in Lever's modern API, an Opportunity represents a candidate's interest in a single posting. A person can have multiple opportunities (one per role). The legacy Candidate endpoint still works but Opportunity is preferred.
…(continued in the in-app connector instructions)
Schritt 2 — Adapter installieren
git clone https://github.com/HelpCode-ai/anythingmcp.git
cd anythingmcp && docker compose up -d
Schritt 3 — Connector in Gemini hinzufügen
Gemini CLI liest MCP-Server aus ~/.gemini/settings.json (oder %APPDATA%\gemini\settings.json unter Windows). Hinzufügen:
{
"mcpServers": {
"anythingmcp": {
"httpUrl": "https://cloud.anythingmcp.com/mcp",
"headers": { "Authorization": "Bearer YOUR_MCP_API_KEY" }
}
}
}
- Hole deinen MCP API Key aus AnythingMCP → Profil → MCP API Keys → Neuer Key.
- Speichern und
geminineu starten. /mcpin Gemini CLI ausführen —Leversollte als verfügbar gelistet sein.- Vertex AI Studio:
https://cloud.anythingmcp.com/mcpimtools-Array der Anfrage mit demselben Bearer-Header übergeben.
Verfügbare Tools
| Tool | What it does |
|---|---|
lever_list_opportunities | List opportunities (candidate × posting) |
lever_get_opportunity | Get one opportunity with full contact, links, tags, applications |
lever_create_opportunity | Create an opportunity (candidate with associated posting) |
lever_update_opportunity_stage | Move an opportunity to a different stage |
lever_archive_opportunity | Archive an opportunity with an archive reason |
lever_list_postings | List job postings |
lever_list_stages | List pipeline stages |
lever_list_users | List Lever users (recruiters, hiring managers) |
lever_list_archive_reasons | List archive reasons configured in the org |
lever_list_feedback | List interview feedback forms attached to an opportunity |
FAQ
Unterstützen Gemini 1.5 Pro oder 2.x MCP? Ja — Gemini CLI ≥ 0.4 und die Vertex AI Tools API akzeptieren MCP httpUrl-Connectors mit Bearer-Header.
Nächste Schritte
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