Salesforce MCP Server for Pydantic AI 12 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Salesforce 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 "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Salesforce?"
)
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 MCP Server
Connect your Salesforce CRM to any AI agent and manage your entire sales pipeline through natural conversation.
Pydantic AI validates every Salesforce tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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
- SOQL Queries — Execute any SOQL query to retrieve data across all objects
- Account Management — List, view, create, and update accounts
- Contact & Lead Management — Browse contacts, search across all objects
- Opportunity Tracking — Monitor pipeline, create and update deals
- Reports — List and execute Salesforce reports
- Full CRUD — Create, read, update, and delete any SObject type
- Global Search — Full-text search across all Salesforce data
The Salesforce 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.
How to Connect Salesforce to Pydantic AI via MCP
Follow these steps to integrate the Salesforce 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 12 tools from Salesforce with type-safe schemas
Why Use Pydantic AI with the Salesforce MCP Server
Pydantic AI provides unique advantages when paired with Salesforce 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 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 connection logic from agent behavior for testable, maintainable code
Salesforce + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Salesforce MCP Server delivers measurable value.
Type-safe data pipelines: query Salesforce with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Salesforce tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Salesforce and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Salesforce responses and write comprehensive agent tests
Salesforce MCP Tools for Pydantic AI (12)
These 12 tools become available when you connect Salesforce to Pydantic AI via MCP:
create_record
Provide JSON fields as a string. Create a new Salesforce record
delete_record
This action is irreversible. Delete a Salesforce record
describe_object
Useful for understanding data structure. Get metadata about a Salesforce object
get_record
Specify the SObject type (Account, Contact, Opportunity, Case, Lead) and the record ID. Get a specific Salesforce record by type and ID
global_search
Returns matches across Accounts, Contacts, Leads, and other objects simultaneously. Search across all Salesforce objects
list_accounts
List Salesforce accounts
list_contacts
List Salesforce contacts
list_opportunities
List sales opportunities
list_reports
List available Salesforce reports
run_report
Use list_reports first to find the report ID. Execute a Salesforce report and get results
soql_query
Example: SELECT Id, Name FROM Account WHERE Industry = 'Technology' LIMIT 10 Execute a SOQL query against Salesforce
update_record
Provide the SObject type, ID, and JSON fields to update. Update an existing Salesforce record
Example Prompts for Salesforce in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Salesforce immediately.
"Show me all open opportunities worth over $50,000."
"Create a new lead for John Smith from TechCo, email john@techco.com."
"Run the Monthly Sales Report."
Troubleshooting Salesforce MCP Server with Pydantic AI
Common issues when connecting Salesforce to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiSalesforce + Pydantic AI FAQ
Common questions about integrating Salesforce 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 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 to Pydantic AI
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.