Addepar MCP Server for Pydantic AI 5 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Addepar 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 Addepar "
"(5 tools)."
),
)
result = await agent.run(
"What tools are available in Addepar?"
)
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 Addepar MCP Server
Connect your Addepar account to your AI agent to unlock enterprise-grade investment intelligence and reporting. From auditing portfolio performance to tracking granular transactions and managing complex ownership structures, your agent handles wealth management data through natural conversation.
Pydantic AI validates every Addepar tool response against typed schemas, catching data inconsistencies at build time. Connect 5 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
- Portfolio Intelligence — Retrieve detailed performance and analytics for your clients and entity groups
- Entity Management — List and audit clients, accounts, and investment groups to maintain organizational clarity
- Position Tracking — View real-time holdings and ownership details across your entire investment landscape
- Transaction Auditing — Retrieve and analyze financial transaction logs to ensure accuracy and transparency
- Metadata Insights — Access deep technical metadata for any entity or account directly from your chat interface
The Addepar MCP Server exposes 5 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 Addepar to Pydantic AI via MCP
Follow these steps to integrate the Addepar 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 5 tools from Addepar with type-safe schemas
Why Use Pydantic AI with the Addepar MCP Server
Pydantic AI provides unique advantages when paired with Addepar 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 Addepar integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Addepar connection logic from agent behavior for testable, maintainable code
Addepar + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Addepar MCP Server delivers measurable value.
Type-safe data pipelines: query Addepar with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Addepar tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Addepar and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Addepar responses and write comprehensive agent tests
Addepar MCP Tools for Pydantic AI (5)
These 5 tools become available when you connect Addepar to Pydantic AI via MCP:
get_entity_details
Get details for an entity
get_portfolio_analytics
Get portfolio performance data
get_position_details
View portfolio holdings
list_entities
List clients and accounts
list_transactions
List financial transactions
Example Prompts for Addepar in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Addepar immediately.
"List all active client entities in my Addepar account."
"Show me the performance for 'The Miller Family Office' for the last quarter."
"List the latest 10 transactions for account ID ACCT-123."
Troubleshooting Addepar MCP Server with Pydantic AI
Common issues when connecting Addepar to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiAddepar + Pydantic AI FAQ
Common questions about integrating Addepar 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 Addepar 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 Addepar to Pydantic AI
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.