How do I get JobProgress API credentials?

Log in to your JobProgress account, navigate to Settings > Developer, and generate a new Access Token.

Are estimates and proposals supported?

Yes, you can list and retrieve data for both estimates and proposals using the corresponding tools in this MCP.

Can I see my schedule?

Yes, the list_appointments tool allows you to retrieve scheduled appointments from your JobProgress account.

JobProgress (Leap) MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: JobProgress (Leap)
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect JobProgress (Leap) through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

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 JobProgress (Leap) "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in JobProgress (Leap)?"
    )
    print(result.data)

asyncio.run(main())

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* 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 JobProgress (Leap) MCP Server

Empower your AI agents with JobProgress's (now part of Leap) business management platform for contractors. This MCP server allows you to list and retrieve customers and jobs, track estimates and proposals, manage workflows and tasks, and view appointments directly through the JobProgress API. Ideal for automating construction and home improvement operations.

Pydantic AI validates every JobProgress (Leap) 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 JobProgress (Leap) 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 JobProgress (Leap) to Pydantic AI via MCP

Follow these steps to integrate the JobProgress (Leap) 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 JobProgress (Leap) with type-safe schemas

Why Use Pydantic AI with the JobProgress (Leap) MCP Server

Pydantic AI provides unique advantages when paired with JobProgress (Leap) 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 JobProgress (Leap) integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your JobProgress (Leap) connection logic from agent behavior for testable, maintainable code

JobProgress (Leap) + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the JobProgress (Leap) MCP Server delivers measurable value.

Type-safe data pipelines: query JobProgress (Leap) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple JobProgress (Leap) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query JobProgress (Leap) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock JobProgress (Leap) responses and write comprehensive agent tests

JobProgress (Leap) MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect JobProgress (Leap) to Pydantic AI via MCP:

get_customer

Returns addresses, project history, and custom metadata. Essential for deep intelligence on a customer before preparing estimates or jobs. Retrieves details for a specific customer

get_job

Returns project descriptions, cost estimates, and current stage in the workflow. Use this to analyze a project's progress or provide customer updates. Retrieves details for a specific job

list_appointments

Essential for managing the field service calendar. Lists all scheduled appointments

list_customers

Returns customer names, contact info, and IDs. Use this as the main starting point for customer management or finding a specific client. Lists all customers in JobProgress

list_estimates

Useful for auditing sales performance and identifying pending project approvals. Lists all job estimates

list_jobs

Includes job titles, status, and associated customer IDs. Use this to monitor the project pipeline and upcoming work. Lists all jobs in JobProgress

list_proposals

Useful for monitoring contract acceptance and sales conversions. Lists all job proposals

list_tasks

Essential for helping the user manage their daily to-do list. Lists all tasks

list_users

Useful for identifying assignees or sales reps. Lists all users in the organization

list_workflows

Useful for understanding business processes. Lists all configured workflows

Example Prompts for JobProgress (Leap) in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with JobProgress (Leap) immediately.

"List all active customers in JobProgress."

"Show me the details for job ID '123'."

"Check my appointments for today."

Troubleshooting JobProgress (Leap) MCP Server with Pydantic AI

Common issues when connecting JobProgress (Leap) to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

JobProgress (Leap) + Pydantic AI FAQ

Common questions about integrating JobProgress (Leap) MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an 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?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your JobProgress (Leap) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.