Can I check the details of a specific task through the agent?

Yes. The `get_task_details` tool allows your AI agent to retrieve full metadata for any specific task ID, including its description, current status, assignees, and any custom fields you have configured.

How do I find tasks belonging to a specific folder or project?

You can use the `list_wrike_tasks` tool and provide the unique `folder_id`. Your agent will return all tasks contained within that specific organizational unit, helping you stay focused on a specific project.

Is it possible to see all my team members' contact IDs via chat?

Absolutely. The `list_wrike_contacts` tool retrieves all users and contacts in your Wrike workspace, providing their names and unique contact IDs required for task assignment or mentions.

Wrike MCP Server for Pydantic AI 6 tools — connect in under 2 minutes

Name: Wrike
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 6 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Wrike through the 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 Wrike "
            "(6 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Wrike?"
    )
    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 Wrike MCP Server

Connect your Wrike account to any AI agent and manage your enterprise workflows through natural conversation.

Pydantic AI validates every Wrike tool response against typed schemas, catching data inconsistencies at build time. Connect 6 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

Task Monitoring — List and browse tasks across your entire account or filter by specific folder/project IDs
Deep Task Analysis — Retrieve comprehensive metadata for specific tasks, including descriptions, assignees, and custom fields
Project Navigation — Browse top-level project containers and monitor their current status and organization
Folder Hierarchy — Explore your organizational structure to understand how tasks are grouped and categorized
Team Discovery — List all users and contacts within your Wrike workspace to find IDs for task assignment
Space Access — List all available work areas (spaces) to navigate your team's different departments or functions
Workflow Automation — Quickly find unique task and folder IDs required for building automated project management flows

The Wrike MCP Server exposes 6 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 Wrike to Pydantic AI via MCP

Follow these steps to integrate the Wrike 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 6 tools from Wrike with type-safe schemas

Why Use Pydantic AI with the Wrike MCP Server

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

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

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

Wrike + Pydantic AI Use Cases

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

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

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

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

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

Wrike MCP Tools for Pydantic AI (6)

These 6 tools become available when you connect Wrike to Pydantic AI via MCP:

get_task_details

Retrieves comprehensive details for a specific Wrike task

list_wrike_contacts

Lists all users and contacts within the Wrike workspace

list_wrike_folders

Lists all folders and projects in the Wrike account

list_wrike_projects

Lists all active projects in the account

list_wrike_spaces

Lists all Wrike spaces available to the authenticated user

list_wrike_tasks

You can optionally provide a folder_id to scope the results. Lists tasks in the Wrike account, optionally filtered by folder

Example Prompts for Wrike in Pydantic AI

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

"List all my Wrike projects."

"Show me tasks in the 'Product Launch 2026' folder."

"Get full details for task ID 'IEA...'."

Troubleshooting Wrike MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Wrike + Pydantic AI FAQ

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