JobNimbus MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect JobNimbus through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 JobNimbus "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in JobNimbus?"
)
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 JobNimbus MCP Server
Empower your AI agents with JobNimbus's specialized CRM for contractors. This MCP server allows you to list and retrieve contacts and jobs, manage tasks and workflows, track payments, and view organization users directly through the JobNimbus API. Ideal for automating field service operations and project management.
Pydantic AI validates every JobNimbus tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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 JobNimbus MCP Server exposes 10 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.
How to Connect JobNimbus to Pydantic AI via MCP
Follow these steps to integrate the JobNimbus MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from JobNimbus with type-safe schemas
Why Use Pydantic AI with the JobNimbus MCP Server
Pydantic AI provides unique advantages when paired with JobNimbus 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 JobNimbus integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your JobNimbus connection logic from agent behavior for testable, maintainable code
JobNimbus + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the JobNimbus MCP Server delivers measurable value.
Type-safe data pipelines: query JobNimbus with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple JobNimbus tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query JobNimbus and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock JobNimbus responses and write comprehensive agent tests
JobNimbus MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect JobNimbus to Pydantic AI via MCP:
get_contact
Returns addresses, phone numbers, email, and custom fields. Use this for deep intelligence on a customer before an interaction. Retrieves details for a specific contact
get_job
Returns project descriptions, associated contact IDs, and current workflow status. Use this to analyze project specifics or provide an update on a job. Retrieves details for a specific job
list_boards
Useful for navigating the account structure. Lists all configured boards
list_contacts
Returns names, contact types, and IDs. Use this to identify clients or start a search for a specific customer. Lists all contacts in JobNimbus
list_jobs
Includes job titles, status, and IDs. Essential for monitoring project flow and upcoming work. Lists all jobs in JobNimbus
list_payments
Essential for monitoring revenue and project billing status. Lists all recent payments
list_products
Useful for auditing available services and pricing items. Lists all products and services
list_tasks
Returns task descriptions, due dates, and IDs. Use this to help the user manage their daily workload or audit team activities. Lists all tasks
list_users
Useful for identifying sales reps or project managers. Lists all users in the organization
list_workflows
Useful for understanding the steps in the company's business processes. Lists all configured workflows
Example Prompts for JobNimbus in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with JobNimbus immediately.
"List all active contacts in JobNimbus."
"Show me the latest jobs created."
"Check the status of my active tasks."
Troubleshooting JobNimbus MCP Server with Pydantic AI
Common issues when connecting JobNimbus to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiJobNimbus + Pydantic AI FAQ
Common questions about integrating JobNimbus 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.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect JobNimbus with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect JobNimbus to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.