How do I find my Portal ID?

Use the `list_portals` tool to retrieve all portals you have access to along with their unique IDs.

Which Data Center domains are supported?

You can use any Zoho Data Center domain such as `zoho.com` (US), `zoho.eu` (Europe), `zoho.in` (India), `zoho.com.au` (Australia), or `zoho.jp` (Japan).

Can I update a task name without sending all other fields?

Yes, the `update_task` tool uses the V3 PATCH method, allowing you to perform partial updates by only providing the fields you want to change.

Zoho Projects MCP Server for Pydantic AI 9 tools — connect in under 2 minutes

Name: Zoho Projects
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 9 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Zoho Projects 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 Zoho Projects "
            "(9 tools)."
        ),
    )

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

asyncio.run(main())

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* 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 Zoho Projects MCP Server

Connect your Zoho Projects account to any AI agent to streamline your project management and team collaboration. This MCP server enables your agent to interact with portals, projects, and tasks directly through natural language interfaces using the latest V3 API.

Pydantic AI validates every Zoho Projects tool response against typed schemas, catching data inconsistencies at build time. Connect 9 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

Project Oversight — List all projects within your portals and retrieve detailed configurations and metadata
Task Management — List, retrieve, create, and update tasks across your projects with support for partial updates
Milestone Tracking — Monitor project milestones and their associated target dates to stay on schedule
Team Visibility — List all users and participants registered for a specific project to manage responsibilities
Organization Control — List task lists and portals to maintain a clear picture of your entire project management hierarchy

The Zoho Projects MCP Server exposes 9 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 Zoho Projects to Pydantic AI via MCP

Follow these steps to integrate the Zoho Projects 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 9 tools from Zoho Projects with type-safe schemas

Why Use Pydantic AI with the Zoho Projects MCP Server

Pydantic AI provides unique advantages when paired with Zoho Projects 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 Zoho Projects integration code

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

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

Zoho Projects + Pydantic AI Use Cases

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

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

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

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

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

Zoho Projects MCP Tools for Pydantic AI (9)

These 9 tools become available when you connect Zoho Projects to Pydantic AI via MCP:

create_project

Requires a portal ID and a project name. Create a new project in a portal

create_task

Requires portal ID, project ID, and task name. Create a new task in a project

list_milestones

List all milestones in a project

list_portals

Use this to identify the portal ID for subsequent project and task calls. List all Zoho Projects portals

list_project_users

List all users associated with a project

list_projects

List all projects in a portal

list_task_lists

List all task lists in a project

list_tasks

List all tasks in a project

update_task

Update an existing task

Example Prompts for Zoho Projects in Pydantic AI

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

"List all portals in my Zoho Projects account."

"Show me the tasks for project ID '987654' in portal '123456'."

"Update task ID '101' in project '987654' to 'Completed' status."

Troubleshooting Zoho Projects MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Zoho Projects + Pydantic AI FAQ

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