Leonar's MCP server connects AI assistants like Claude to your recruiting data. Your agent can source candidates, manage pipelines, send outreach, and pull analytics, all through natural language.
MCP is an open standard created by Anthropic that lets AI assistants connect securely to external tools and data sources. Instead of copying data between your CRM and your AI tool, MCP creates a direct, secure bridge between them. Your AI agent reads and writes to Leonar as if it were a native user.
Think of MCP as a universal adapter for AI. Before MCP, every integration between an AI assistant and a business tool required custom code, API wrappers, and ongoing maintenance. MCP replaces all of that with a single, standardized protocol. AI tools like Claude, ChatGPT, and Cursor already support it natively, which means connecting them to Leonar takes minutes instead of weeks of engineering work.
For recruiting teams, this is a game changer. Instead of switching between your CRM, your sourcing tools, and your AI assistant, you can work entirely through natural language. Ask your AI to find candidates, update a pipeline, or draft an outreach message, and it executes the action directly inside Leonar. No copy-pasting, no manual data entry, no context lost between tools.
MCP turns your AI assistant into a recruiting co-pilot. Here are the scenarios where teams see the biggest impact.
Instead of building complex boolean filters manually, describe the candidate you need in plain English. Your AI agent searches across your full candidate database in Leonar, applies the right filters, and returns a ranked shortlist. A search that used to take 15 minutes now takes seconds.
After a round of interviews, tell your AI assistant to move candidates between stages, add interview notes, or flag top performers. The agent updates Leonar in real time, so your pipeline always reflects the latest status without anyone typing into spreadsheets or clicking through forms.
Ask your AI agent to draft personalized emails based on each candidate's profile, experience, and the role you are hiring for. The agent pulls context from Leonar (candidate history, previous interactions, job requirements) and generates messages that feel personal, not templated. Then it launches or schedules the outreach sequence directly inside the platform.
Skip the dashboards and ask your AI questions like "What is our time-to-hire for engineering roles this quarter?" or "Which sourcing channels have the highest conversion rate?" The agent pulls live data from Leonar and gives you answers instantly, making it easy to spot bottlenecks and adjust your strategy on the fly.
Your AI assistant understands your recruiting workflows. Ask in natural language, and it acts directly inside Leonar.
Search your candidate database, apply filters by skills, location, experience, and seniority, and get ranked results in seconds. Your AI agent can also enrich candidate profiles with missing contact details automatically.
"Find senior React developers in Paris with 5+ years of experience"
"Search for product managers who worked at a SaaS company"
"Enrich this candidate's profile with contact information"
Move candidates between stages, add interview notes, update statuses, and keep your hiring pipeline perfectly organized. Your agent handles bulk actions too, so you can update dozens of candidates in a single request.
"Move all candidates from the screening stage who scored above 80 to the interview stage"
"Show me all candidates in the offer stage for the VP Sales role"
"Add a note to Marie Laurent's profile about today's call"
Launch, pause, and manage multi-step outreach sequences directly through your AI assistant. Draft personalized emails, schedule follow-ups, and control every aspect of your candidate communication without leaving your AI tool.
"Start the onsite outreach sequence for my top 10 sourced candidates"
"Draft a follow-up email for candidates who haven't replied in 5 days"
"Pause the outreach sequence for candidates who moved to interview"
Ask questions about your recruiting performance and get instant answers. Your AI agent queries Leonar's analytics engine and reports on response rates, pipeline velocity, conversion rates, and team performance in real time.
"What's my team's response rate this month compared to last month?"
"How many candidates moved to offer stage this quarter?"
"Show me the pipeline conversion rates for the Engineering job"
Connect your AI assistant to Leonar with a simple configuration. No custom code, no engineering team, no deployment process required.
Generate a scoped API key from your Leonar dashboard with the permissions your agent needs. You control exactly which data and actions your AI can access: read-only for analytics, full access for pipeline management, or anything in between.
Open your AI assistant's settings and add the Leonar MCP server URL with your API key. It is a single configuration entry. No SDKs to install, no webhooks to configure, no middleware to maintain.
Your AI agent now has direct access to your candidates, pipelines, conversations, and outreach tools. Start by asking it to search for candidates or check your pipeline status. It works immediately.
The Leonar MCP server is compatible with any AI assistant that supports the Model Context Protocol.
The same enterprise-grade security as our REST API protects every MCP connection.
No. Setting up the MCP server requires copying a URL and an API key into your AI assistant's settings. There is no coding involved. If you can use Claude or ChatGPT, you can connect them to Leonar through MCP. The entire setup takes less than five minutes.
Leonar's MCP server works with any AI tool that supports the Model Context Protocol. This includes Claude by Anthropic, ChatGPT by OpenAI, Cursor, and any custom AI agent built with MCP support. As more tools adopt the standard, they automatically become compatible with Leonar.
Absolutely. The MCP connection uses the same enterprise-grade security as Leonar's REST API. All data is encrypted in transit and at rest. You control permissions through scoped API keys, and every action your agent takes is logged in a full audit trail. Leonar is GDPR compliant with EU data residency.
You have full control over what your agent can do. API keys are scoped with specific permissions, so you can grant read-only access for analytics, or enable write access only for specific actions like adding notes or moving candidates between stages. The agent can only perform actions you have explicitly authorized.
The Leonar API is designed for developers who want to build custom integrations programmatically. The MCP server is designed for end users who want their AI assistant to interact with Leonar through natural language. With MCP, you do not write any code. You simply talk to your AI, and it translates your requests into the right API calls behind the scenes.
Every action the AI agent takes through MCP is logged and visible in your Leonar dashboard. If something looks wrong, you can review the audit trail and undo any changes. The AI also confirms important actions before executing them, so you always have the final say on critical operations like bulk updates or outreach launches.
Connect your AI assistant to Leonar and let it recruit alongside your team.