How do I find my Workspace and Model IDs?

You can use the `list_workspaces` and `list_models` tools provided by this server. They will return a list of all accessible environments along with their unique IDs.

Are actions in Anaplan synchronous or asynchronous?

Most data actions (imports, exports, processes) are asynchronous. When you run them, they return a Task ID. You should then use `get_task_status` to monitor the progress until it reaches a 'COMPLETE' state.

Can I trigger an Anaplan process that contains multiple actions?

Yes, use the `run_process` tool. Processes in Anaplan are designed to run a sequence of imports, exports, and other actions in a specific order. You can monitor the entire process using the returned Task ID.

Anaplan MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Anaplan
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 Anaplan through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

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 Anaplan "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Anaplan MCP Server

Connect your Anaplan account to your AI agent to automate financial planning, supply chain, and sales operations. This MCP server allows you to discover workspaces and models, and trigger complex data integration tasks using natural language.

Pydantic AI validates every Anaplan 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.

What you can do

Workspace & Model Discovery — List all available workspaces and models to navigate your planning environment.
Execute Data Actions — Trigger and monitor imports, exports, and processes (groups of actions) to move data in and out of Anaplan.
Task Monitoring — Real-time tracking of asynchronous task statuses to ensure your data integrations complete successfully.
File Management — List files within your models to keep track of historical imports and exports.

The Anaplan 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 Anaplan to Pydantic AI via MCP

Follow these steps to integrate the Anaplan 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 Anaplan with type-safe schemas

Why Use Pydantic AI with the Anaplan MCP Server

Pydantic AI provides unique advantages when paired with Anaplan 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 Anaplan integration code

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

Dependency injection system cleanly separates your Anaplan connection logic from agent behavior for testable, maintainable code

Anaplan + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Anaplan MCP Server delivers measurable value.

Type-safe data pipelines: query Anaplan with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Anaplan tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Anaplan and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Anaplan responses and write comprehensive agent tests

Anaplan MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Anaplan to Pydantic AI via MCP:

get_task_status

Get status of a running task

list_exports

List export actions for a model

list_files

List files in a model (exports/imports)

list_imports

List import actions for a model

list_models

List Anaplan models. Optionally filter by workspaceId

list_processes

List processes for a model

list_workspaces

List available Anaplan workspaces

run_export

Run an Anaplan export action

run_import

Run an Anaplan import action

run_process

Run an Anaplan process

Example Prompts for Anaplan in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Anaplan immediately.

"List all my Anaplan workspaces and models."

"Run the 'Monthly Actuals' import in the Finance workspace."

"What's the status of the process task 'p_456'?"

Troubleshooting Anaplan MCP Server with Pydantic AI

Common issues when connecting Anaplan to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Anaplan + Pydantic AI FAQ

Common questions about integrating Anaplan 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 Anaplan MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.