Procore MCP Server for Pydantic AI 8 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Procore 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 Procore "
"(8 tools)."
),
)
result = await agent.run(
"What tools are available in Procore?"
)
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 Procore MCP Server
Connect your Procore construction management platform to any AI agent and oversee projects, quality, and field operations through natural conversation.
Pydantic AI validates every Procore tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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.
What you can do
- Projects Overview — List all active construction projects with status, addresses, timelines, and budget summaries
- RFIs & Submittals — Track Requests for Information and material approvals with assignees, due dates, and response histories
- Field Observations — Review safety and quality observations from the jobsite including priority, photos, and corrective actions
- Punch Lists — Monitor deficiencies to resolve before closeout with locations, assignees, and deadlines
- Daily Logs — Access daily logs with weather, workforce counts, equipment usage, and delay notes
- Drawings — Browse blueprints, elevations, and shop drawings with revision tracking
The Procore MCP Server exposes 8 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 Procore to Pydantic AI via MCP
Follow these steps to integrate the Procore 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 8 tools from Procore with type-safe schemas
Why Use Pydantic AI with the Procore MCP Server
Pydantic AI provides unique advantages when paired with Procore 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 Procore integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Procore connection logic from agent behavior for testable, maintainable code
Procore + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Procore MCP Server delivers measurable value.
Type-safe data pipelines: query Procore with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Procore tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Procore and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Procore responses and write comprehensive agent tests
Procore MCP Tools for Pydantic AI (8)
These 8 tools become available when you connect Procore to Pydantic AI via MCP:
get_project
Includes budget, schedule, team, and project settings. Get project details
list_daily_logs
Includes weather, workforce count, equipment, notes, and delays. List daily construction logs
list_drawings
Includes discipline, set, revision, and approval status. List project drawings
list_observations
Includes type, priority, assignee, photos, and status. List field observations
list_projects
List all construction projects
list_punch_items
Includes description, location, assignee, due date, and status. List punch list items
list_rfis
Includes subject, status, assignee, due date, and response history. List RFIs for a project
list_submittals
Includes title, spec section, status, and approver. List submittals
Example Prompts for Procore in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Procore immediately.
"Show me all my active construction projects."
"List all overdue RFIs on the Skyline Tower project."
"How many open punch items on Harbor View?"
Troubleshooting Procore MCP Server with Pydantic AI
Common issues when connecting Procore to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiProcore + Pydantic AI FAQ
Common questions about integrating Procore 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 Procore 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 Procore to Pydantic AI
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.