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.
Quick answer: Leonar MCP lets Claude, ChatGPT, GitHub Copilot and any MCP-compatible agent read and update recruiting data through structured tools. Agents can search candidates, review projects, draft outreach and update pipeline records without screen scraping.
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"
For Claude Desktop and Claude.ai, add the hosted connector URL and authorize your workspace through Leonar OAuth. Local clients can use an API key fallback.
In Claude Desktop or Claude.ai, open Settings / Customize > Connectors, choose Add custom connector, and enter https://app.leonar.app/api/mcp. Do not use the old SSE URL.
Claude discovers Leonar OAuth from the endpoint, redirects you to Leonar, and asks which workspace the connector may access. This flow does not require a Leonar API key.
Claude Code, Cursor, Codex, and generic MCP clients can connect with Direct HTTP Bearer auth or the local @leonar/mcp NPX bridge using a leo_... API key.
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. For Claude Desktop and Claude.ai, setup means adding https://app.leonar.app/api/mcp as a custom connector, signing in to Leonar, and authorizing one workspace. A Leonar API key is only needed for local or non-OAuth MCP clients.
Leonar's MCP server works with MCP clients that support Streamable HTTP or a local stdio bridge. Claude Desktop and Claude.ai should use the remote OAuth connector. Claude Code, Cursor, Codex, and generic clients can use Direct HTTP or the @leonar/mcp NPX bridge.
Yes. Claude remote connectors use Leonar OAuth tokens scoped to a single workspace. API-key clients use the same leo_... keys and scopes as the REST API. All requests are rate limited, checked against billing access, and bound to workspace membership.
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 REST API is for developers building integrations directly. MCP exposes curated recruiting tools and resources to AI assistants over https://app.leonar.app/api/mcp, with OAuth for Claude remote connectors or Bearer API keys for local clients.
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.
Practical guides for sourcing with Claude, connecting MCP to your recruiting stack, and using AI agents to grow your agency.
Learn the clean way to source candidates in LinkedIn Recruiter with Claude AI, why browser bots fail, and how a structured tool does it reliably.
Use AI agents like Claude and ChatGPT to find, target, and win new clients for your staffing agency. Includes prompts, connected workflows, and templates.
Use Leonar's open API and MCP protocol to connect Claude, ChatGPT, or any AI agent to your recruiting CRM. Step-by-step guide with real use cases.
Connect your AI assistant to Leonar and let it recruit alongside your team.