Recruit CRM MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Create Candidate, Create Job, Get Candidate Details, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Recruit CRM through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The Recruit CRM app connector for Pydantic AI is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Recruit CRM "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Recruit CRM?"
)
print(result.data)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Recruit CRM MCP Server
What you can do
- List and manage candidates in your recruitment database in real-time.
- Track job vacancies, requirements, and application pipelines.
- Access client company details and key contacts directly from your AI agent.
- Create new candidates and job postings with simple commands.
Who is it for?
- Recruitment agencies looking for automated ATS and CRM control.
- HR teams managing a high volume of candidates and job postings.
- Hiring managers tracking pipeline status and decision makers.
Pydantic AI validates every Recruit CRM tool response against typed schemas, catching data inconsistencies at build time. Connect 12 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
The Recruit CRM MCP Server exposes 12 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 Recruit CRM tools available for Pydantic AI
When Pydantic AI connects to Recruit CRM through Vinkius, your AI agent gets direct access to every tool listed below — spanning recruitment, ats, crm, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Add a new candidate
Create a new job posting
Get details of a specific candidate
Get details of a specific company
Get details of a specific contact
Get details of a specific job
Get account information
List recruitment candidates
List client companies
List client contacts
List candidates assigned to a job
List job vacancies
Connect Recruit CRM to Pydantic AI via MCP
Follow these steps to wire Recruit CRM into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Recruit CRM MCP Server
Pydantic AI provides unique advantages when paired with Recruit CRM through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Recruit CRM integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Recruit CRM connection logic from agent behavior for testable, maintainable code
Recruit CRM + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Recruit CRM MCP Server delivers measurable value.
Type-safe data pipelines: query Recruit CRM with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Recruit CRM tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Recruit CRM and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Recruit CRM responses and write comprehensive agent tests
Example Prompts for Recruit CRM in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Recruit CRM immediately.
"List all active jobs in Recruit CRM."
"Show me all candidates in the final interview stage across all open positions."
"Add a new candidate to the Senior Backend Engineer position and schedule a first-round interview."
Troubleshooting Recruit CRM MCP Server with Pydantic AI
Common issues when connecting Recruit CRM to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiRecruit CRM + Pydantic AI FAQ
Common questions about integrating Recruit CRM MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.