Lever MCP. Manage your entire hiring pipeline via natural language.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Lever MCP Server connects your AI agent directly to the Lever ATS API. Use it to list job postings, create new opportunities, access candidate profiles, and move applications through any stage of the hiring pipeline—all from chat or your IDE.
What your AI agents can do
Archive hiring opportunity
Marks an application opportunity as archived in the system.
Create hiring opportunity
Creates a brand new candidate application record using specified details.
Create job posting
Generates and publishes a new job advertisement to Lever.
List all existing job postings or generate a completely new one using list_job_postings and create_job_posting.
View all current candidate applications (list_hiring_opportunities) and move them to a specific stage in the hiring pipeline via update_opportunity_stage.
Fetch comprehensive details, history, and contact info for any single candidate using get_candidate_profile.
Create a new application record (create_hiring_opportunity) or pull detailed status information on an existing opportunity (get_opportunity_details).
List all defined hiring stages (e.g., Screen, Interview) configured in your Lever account using list_hiring_stages.
Ask AI about this MCP
Supported MCP Clients
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Lever MCP Server: 10 Tools for Recruitment Workflow
These tools let your agent interact with every core function of the Lever ATS—from creating job postings to moving applications through stages.
019d75c6archive hiring opportunity
Marks an application opportunity as archived in the system.
019d75c6create hiring opportunity
Creates a brand new candidate application record using specified details.
019d75c6create job posting
Generates and publishes a new job advertisement to Lever.
019d75c6get candidate profile
Retrieves all personal details and interaction history for one candidate.
019d75c6get opportunity details
Pulls the complete, specific data set for a single job application opportunity.
019d75c6get posting details
Retrieves all details and current status of one specific job advertisement.
019d75c6list hiring opportunities
Gets a list summary of every active candidate application in the system.
019d75c6list hiring stages
Returns a list of all defined steps or phases (like 'Screen' or 'Interview') in your hiring pipeline.
019d75c6list job postings
Lists and retrieves the names and statuses of every job posting you have created.
019d75c6update opportunity stage
Moves a candidate opportunity from its current status to a different stage in the pipeline.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Lever, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Listen up. The Lever MCP Server plugs your AI agent straight into the Lever ATS API. You're gonna be able to list job postings, spin up new opportunities, dig into candidate profiles, and move applications through whatever stage of hiring you're on—all from chat or right in your IDE. Forget clicking around in the Lever UI; you just tell your agent what needs doing, and it executes the calls.
Control Job Postings
You can get a list summary of every job posting you have with list_job_postings, or if you need to crank out something new, you'll use create_job_posting to generate and publish a fresh ad.
Track Candidate Status & Pipeline Management
Need an overview of who’s in the system? You'll hit up list_hiring_opportunities to get a list summary of every active application. If you wanna move a candidate, say from 'Screening' to 'Interview,' you use update_opportunity_stage, which moves that specific opportunity record to your defined stage. Before you do any of that, remember you can check out all the stages configured in your account by calling list_hiring_stages.
Manage Opportunities & Profiles
When you're focused on a single candidate or job opening, you have tools for deep dives. You can grab the complete, specific data set for one opportunity using get_opportunity_details. If you need to start tracking someone new, create_hiring_opportunity lets your agent build that record right away with specified details. For candidates, you'll get all their personal info and interaction history—the whole nine yards—by running get_candidate_profile.
If an opportunity is dead or closed out, you mark it as archived in the system using archive_hiring_opportunity.
The Full Workflow
Here’s how your agent handles the flow. You can check all existing job postings by calling list_job_postings, and then if a new role pops up, you'll use create_job_posting. When you spot a promising candidate, you run get_candidate_profile to see their history; if they become an active lead, your agent can create the record using create_hiring_opportunity.
You check out all current applications with list_hiring_opportunities, then use update_opportunity_stage to push that candidate through a defined phase. If you need more context on one specific application, you pull the full data set via get_opportunity_details. Don't forget you can always check what phases are available by calling list_hiring_stages. You even mark opportunities as closed out with archive_hiring_opportunity.
It’s all about having your agent directly execute these API calls, letting you skip the UI clicks and just talk workflow into existence.
How Lever MCP Works
- 1 Subscribe to the server and provide your unique Lever API key.
- 2 Your AI client sends a request (e.g., 'Find me all candidates who finished the interview stage').
- 3 The agent executes the necessary tools (like
list_hiring_opportunitiesfollowed by filtering) and returns the requested data.
The bottom line is, your AI client handles the API calls; you just talk to it normally.
Who Is Lever MCP For?
Recruiters who hate switching between their ATS and development environment. Hiring Managers tired of manually asking for status updates. HR Ops running bulk data tasks that require precise, structured inputs.
Uses this to check a candidate's full history (get_candidate_profile) and draft new job descriptions based on existing postings.
Updates application statuses instantly using update_opportunity_stage or archives old leads with archive_hiring_opportunity without leaving their chat window.
Asks the agent to list all opportunities for a specific role (list_job_postings) and get a status report on key applicants.
What Changes When You Connect
- Stop switching tabs. You can update a candidate's status using
update_opportunity_stage—moving them from 'Screening' to 'Interview'—without ever leaving your terminal or chat interface. - Need job data? Use
list_job_postingsand then dive into specifics withget_posting_details. You get all the meta-info about a job ad instantly, which is faster than checking the web UI. - Candidate history matters. Running
get_candidate_profilegives you Jane Smith's full record, including contact info and every interaction point, all in one API call. - Automate data entry. Instead of manually filling out forms for a new applicant, your agent uses
create_hiring_opportunity, letting you input the details directly via natural language prompts. - Always know where you are. Use
list_hiring_stagesfirst to confirm the correct pipeline names before running any status update tool. This prevents common state errors.
Real-World Use Cases
Status Check for a Referral
The recruiter got a referral ID and needs to know where they stand. They ask their agent, 'Check the opportunity status for candidate X.' The agent runs get_opportunity_details and reports back exactly which stage (and who owns it) without needing the recruiter to navigate multiple screens in Lever.
Cleaning Up Old Leads
The team just finished a hiring round, and 50 old applications need to be moved out of the active view. Instead of manually updating them all, the agent runs list_hiring_opportunities to grab the IDs, then uses archive_hiring_opportunity for batch cleanup.
Starting a New Role
The hiring manager needs a new role posted. They tell the agent, 'Post a job for Senior DevOps.' The agent executes create_job_posting, handling all the required JSON formatting and making the job live instantly.
Candidate Data Sync
A candidate is found but has no active opportunity. The sourcer asks, 'Get Jane Doe's profile.' The agent uses get_candidate_profile to pull her data, which can then be used by the agent to initiate a new application using create_hiring_opportunity.
The Tradeoffs
Skipping Profile Retrieval
Trying to create an opportunity for someone without first checking if they exist. You might just guess the ID or miss crucial contact data, leading to incomplete records.
→
Always use get_candidate_profile first on a known candidate name or email address. This validates their existence and pulls all necessary details before running create_hiring_opportunity.
Manual Status Guesswork
Assuming the correct stage name (e.g., calling it 'Interviewing' when Lever calls it 'In-Review'). This causes API failures and wasted time.
→
Run list_hiring_stages first. Use the exact names returned by that tool—like 'Interview' or 'Offer'—when calling update_opportunity_stage.
Over-complicating a Simple List
Writing a massive, multi-step prompt to list everything. The agent gets bogged down and only returns partial data.
→
Keep it simple: 'List all my active job postings.' Use list_job_postings. It's designed for quick reads.
When It Fits, When It Doesn't
Use this server if your core pain point is moving structured, discrete records (Job Posts, Opportunities, Profiles) through a known lifecycle. You need to enforce state transitions—like moving an opportunity from 'Screening' to 'Interview.'
Don't use it if you just need general reporting or unstructured data mining across all company departments; other database connectors might be better for that. Also, don't try to build complex business rules (e.g., 'If the candidate has 5 years experience AND is in NYC, then send a bonus'). This server manages data movement, not business logic. For true workflow enforcement across multiple tools, you need client-side orchestration using these atomic steps.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Lever. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Updating candidate status shouldn't require navigating three different screens.
Right now, updating a single application requires logging into Lever. You have to find the candidate's name or ID, pull up their opportunity record, click 'Status,' select the new stage from a dropdown menu (maybe even checking if it's available), and finally hit save. It takes clicks, context switching, and time.
With this MCP server, you just tell your agent: 'Move opp-123 to Interview.' The agent runs the `update_opportunity_stage` tool. Done. No UI navigation. You get immediate confirmation that the state changed correctly.
Lever MCP Server: Manage postings, candidates & stages
The old way of generating a job posting meant filling out forms in Lever, uploading documents, and manually setting pay ranges. It was rigid—if you changed one detail, the whole flow could break.
Now, your agent handles it. You tell the server to 'Create a new job for X role.' The agent uses `create_job_posting` and manages all the underlying data structure required by Lever. It's just that simple.
Common Questions About Lever MCP
How do I list my active jobs using the Lever MCP Server? +
Use the list_job_postings tool. It fetches and returns all job postings currently configured in your account so you know what's running.
What is the best way to move an opportunity stage with Lever MCP Server? +
You must use the update_opportunity_stage tool. To avoid errors, always run list_hiring_stages first to get the exact, current pipeline names.
Can I create a new candidate opportunity with Lever MCP Server? +
Yes, use the create_hiring_opportunity tool. It requires you to pass all necessary details in a structured JSON body so the record is created correctly from the start.
Which tool do I use to get detailed info on one candidate? +
Use get_candidate_profile. This pulls comprehensive data about a person—their contact details, history, and all linked opportunities.
What credentials do I need before using `list_job_postings`? +
You must supply a valid Lever API Key. This key authenticates your AI client, allowing it to access and read data from your specific account. Don't forget to enter this during the initial setup.
Before using `update_opportunity_stage`, how do I see all my configured pipeline steps? +
Use the list_hiring_stages tool. It retrieves every defined stage in your Lever account—like 'Screen' or 'Interview.' This ensures you pass the correct destination ID when moving a candidate.
When using `create_hiring_opportunity`, what happens if I miss required JSON fields? +
The tool will return an immediate validation error. You need to provide a full JSON body with all mandatory details, like the candidate's name and source, for the record to create successfully.
What kind of data does `get_posting_details` retrieve about a job listing? +
It pulls every configured detail for that single job post. This includes descriptions, location requirements, and specific dates—it's much more granular than just viewing the list.
How do I move a candidate to a specific stage? +
Use the update_opportunity_stage tool with the unique opportunity ID and the target stage ID. You can find stage IDs using the list_hiring_stages tool.
Can I archive an application via the agent? +
Yes, use the archive_hiring_opportunity tool. You will need to provide the opportunity ID and a valid archive reason ID.
Is it possible to see a candidate's contact information? +
Absolutely. Use the get_candidate_profile tool with the candidate's unique ID to retrieve their full profile, including email, phone, and links.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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