Salesforce Commerce Cloud 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 Salesforce Commerce Cloud through the 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 Salesforce Commerce Cloud "
"(8 tools)."
),
)
result = await agent.run(
"What tools are available in Salesforce Commerce Cloud?"
)
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 Salesforce Commerce Cloud MCP Server
Connect Salesforce Commerce to any AI agent.
Pydantic AI validates every Salesforce Commerce Cloud tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through the 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
- Products — Search by name/code, filter by family, update catalog items
- Orders — Search by number/account, filter by status, view line items
- Price Books — List price books and view pricing entries
The Salesforce Commerce Cloud 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 Salesforce Commerce Cloud to Pydantic AI via MCP
Follow these steps to integrate the Salesforce Commerce Cloud 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 Salesforce Commerce Cloud with type-safe schemas
Why Use Pydantic AI with the Salesforce Commerce Cloud MCP Server
Pydantic AI provides unique advantages when paired with Salesforce Commerce Cloud 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 Salesforce Commerce Cloud integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Salesforce Commerce Cloud connection logic from agent behavior for testable, maintainable code
Salesforce Commerce Cloud + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Salesforce Commerce Cloud MCP Server delivers measurable value.
Type-safe data pipelines: query Salesforce Commerce Cloud with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Salesforce Commerce Cloud tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Salesforce Commerce Cloud and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Salesforce Commerce Cloud responses and write comprehensive agent tests
Salesforce Commerce Cloud MCP Tools for Pydantic AI (8)
These 8 tools become available when you connect Salesforce Commerce Cloud to Pydantic AI via MCP:
sf_list_pricebooks
Returns price book name, description, active status, and IsStandard flag. Every Salesforce org has a Standard Price Book. Additional price books allow different pricing for channels, regions, or customer tiers (e.g., "Partner Pricing", "Enterprise Discount"). Use to find price book IDs before viewing entries. List all price books in Salesforce with name, description, active status, and whether it is the standard price book
sf_order_items
Returns product name, quantity, unit price, total price, and description per line item. Use when the user asks "what is in this order?", needs to review order composition, or wants to verify pricing before activation. Get all line items of a specific Salesforce order — products, quantities, unit prices, and total prices per item
sf_orders_by_status
Use for order management: "how many draft orders need activation?", "show all activated orders", or for revenue analysis by order status. Get Salesforce orders filtered by status (Draft or Activated) for order management and fulfillment tracking
sf_pricebook_entries
Returns product name, product code, unit price, currency, and active status. Price book entries define the actual price of a product in a specific context (channel, region, tier). Use to check pricing, compare across price books, or verify product availability in a specific price book. Get all product price entries within a specific price book — products with their unit prices and active status
sf_products_by_family
Returns products within a category (e.g., "Hardware", "Software", "Services"). Use when the user asks about products in a specific category, wants a category-level view, or needs to browse the catalog by family. Get all active products within a specific product family for category-level catalog browsing
sf_search_orders
Returns order number, account name, status (Draft/Activated), total amount, effective date, and order owner. Orders represent confirmed customer transactions. Use when the user asks about customer orders, wants to look up a specific order number, or needs to review order history. Search Salesforce orders by order number or account name to find transactions with status, total, and dates
sf_search_products
Returns product name, product code (SKU), product family, description, and whether the product is active. Products define what can be sold — they are linked to price books for pricing. Use when the user asks about product catalog, wants to find a specific product, or needs product IDs for orders. Search the Salesforce product catalog by name or product code to find items with family, description, and active status
sf_update_product
Common operations: set IsActive to false to discontinue a product, change Family to reclassify, update Description, or rename. Only specified fields change. Update a product in the Salesforce catalog — change name, description, active status, product code, or family
Example Prompts for Salesforce Commerce Cloud in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Salesforce Commerce Cloud immediately.
"Search for all products in the Enterprise family"
"Show all draft orders"
"What items are in order ORD-001?"
Troubleshooting Salesforce Commerce Cloud MCP Server with Pydantic AI
Common issues when connecting Salesforce Commerce Cloud to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiSalesforce Commerce Cloud + Pydantic AI FAQ
Common questions about integrating Salesforce Commerce Cloud 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 Salesforce Commerce Cloud 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 Salesforce Commerce Cloud to Pydantic AI
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.