Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Search public Lever job boards: resolve a company, read its openings, read one in full.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Die .mcpb-Datei des Entwicklers herunterladen
Der Link führt zur Datei des Entwicklers selbst; wir hosten sie nicht und verpacken sie nicht neu. Öffne die Datei, dann installiert Claude Desktop sie.
Führe das in deinem Terminal aus
claude mcp add lever -- npx -y mcp-leverIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"lever": {
"command": "npx",
"args": [
"-y",
"mcp-lever"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"lever": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mcp-lever"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto smeet666 bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (2.1.0) kam vor 9 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js, MCPB auf deinem Computer.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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Connect AI agents to Exa for web search, content fetching, and multi-step research.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
Lever is recruiting software that thousands of companies use to run their hiring, and every customer gets a public job board that comes with it. Each board carries that company's open positions with their title, their location, the team and department they sit in, the commitment they ask for, the full advert, and the salary range where the company chose to publish one. Lever hosts one board per company, on either its global or its European instance, and publishes no index across them.
This server connects a chat client to those boards. You name the companies you are interested in, and it turns each name into the site name that addresses its board, searches their openings, filters them by location, team, workplace type, country, salary or how recently they were posted, reads one opening in full, and lists the wordings each company filters by. It needs no API key and no account.
_Version française_
One-click install
Claude Code
claude mcp add lever -- npx -y mcp-lever
Claude Desktop, Cursor, and any client using the standard config format
{
"mcpServers": { "lever": { "command": "npx", "args": ["-y", "mcp-lever"] } } }
Node 24 or later is required, and no environment variable has to be set.
{
"mcpServers": { "lever": { "command": "docker", "args": ["run", "-i", "--rm", "ghcr.io/smeet666/mcp-lever:2.1.0"] } } }
-i keeps stdin open, which is where the protocol travels, and -t is left out because a TTY rewrites the stream. The container needs outbound HTTPS to api.lever.co and api.eu.lever.co, and nothing else: no volume, no port, no credential.
Download mcp-lever-2.1.0.mcpb from the latest release and open it. A client that supports MCP bundles installs it on its own, with no npm and no configuration file to edit. The bundle carries its dependencies, so nothing is fetched at install time.
Every question starts from a company, since Lever offers no search across boards. search_jobs resolves the names you give it, so no preparation is needed:
resolve_company(["Included Health"]) -> includedhealth, global instance, publishing
search_jobs(["Included Health"], keyword: "therapist") get_job("includedhealth", "6f97a19f-…")
| Tool | What it does |
|---|---|
resolve_company | Turns company names into the Lever site names of their boards. |
search_jobs | Searches the openings of the companies you name. |
get_job | Reads one opening in full, advert included. |
list_filter_values | Lists the wordings one company files its openings under. |
A Lever site name distinguishes case, so Flex answers where flex returns nothing. Four spellings are tried per name on each of the two instances, and the answer lists what was sent, so nothing found is never proof that a company is absent from Lever.
resolve_companyTurns company names into Lever site names, reporting every instance that answered. It takes a list.
| Argument | Type | Required | What it does |
|---|---|---|---|
names | array of 1 to 25 strings | yes | Company names, or Lever site names you already know. |
In return: one entry per name, carrying input; found, a list of { slug, instance, publishes } where publishes is false for a site that exists and lists nothing today; tried, the spellings sent in order; and cached, true when this session had already resolved that name. A name answering on both instances comes back with both, and neither is elected: pass the one you mean to the other tools.
search_jobsSearches the openings of the companies named. Lever applies the filters it supports on its own exact wording, and this server applies the rest to the openings it read.
| Argument | Type | Required | What it does |
|---|---|---|---|
companies | array of 1 to 25 strings | yes | Company names or Lever site names. Each is resolved here. |
keyword | string | no | Words to look for in the title and the advert. |
location | array of 1 to 20 strings | no | Locations, exactly as Lever writes them. |
team | array of 1 to 20 strings | no | Teams, exactly as Lever writes them. |
department | array of 1 to 20 strings | no | Departments, exactly as Lever writes them. |
commitment | array of 1 to 20 strings | no | Commitments, exactly as Lever writes them. |
workplace_type | array of 1 to 4 strings | no | remote, hybrid, onsite or unspecified. |
country | array of 1 to 20 two-letter codes | no | Countries as ISO codes, as in FR or US. |
salary_min | number, 0 or more | no | The lowest upper bound of a salary range to keep. |
salary_interval | string | no | The period salary_min is written in, such as per-year-salary. |
currency | three-letter code | no | The currency salary_min is written in, as in EUR. |
posted_within_days | integer, 1 to 3650 | no | How recent an opening must be. |
limit | integer, 1 to 100, default 25 | no | Openings to read per company. |
skip | integer, 0 to 100000, default 0 | no | Openings to step over per company. |
Lever itself applies location, team, department and commitment; this server applies keyword, workplace_type, country, salary_min, salary_interval, currency and posted_within_days to what it read. list_filter_values publishes the wordings the first four take, and a wording Lever does not know comes back as an empty list.
In return: jobs, each carrying id and company_slug, which get_job takes, plus title, location, all_locations, country, workplace_type, team, posted_at, url and apply_url. commitment and department are absent when the company records neither. salary is null for an opening published without one, which is never the same as zero, and it carries the interval Lever wrote it in, never converted or annualised. per_company gives one outcome per company, with a status of read, unresolved, empty or failed, which are four different answers, and the read and returned counts around the filters. total_available is always null: Lever publishes no result count. The rows carry no advert text, since one company's board can run to megabytes.
limit applies per company, and a company whose openings fill it may publish more: the notes say when that happened, and that a count taken inside that window measures the window. posted_within_days walks up to five pages per company, and Lever pages by title, so an opening published yesterday can sit anywhere in a board.
get_jobReads one opening in full: the advert, its named sections, and the salary as published.
| Argument | Type | Required | What it does |
|---|---|---|---|
company_slug | string | yes | The Lever site name, as resolve_company returns it. |
job_id | string | yes | The identifier of one opening, as a search returns it. |
instance | global or eu | no | The instance the row came from. The global one by default. |
In return: job, holding the fields a search row carries, plus description, sections as { heading, items }, salary_note for what the company wrote beside the range, and source with the address it was retrieved from.
list_filter_valuesLists the team, location and commitment wordings one company uses. Read it before filtering: Lever matches its own wording, and the vocabulary belongs to each company, one writing Full-time where another writes EE Full-Time.
| Argument | Type | Required | What it does |
|---|---|---|---|
company_slug | string | yes | The Lever site name, as resolve_company returns it. |
| instance | global or eu | no
Nur der Anfang wird gezeigt; den Rest findest du im Repo