How to Use the Zoho ZeptoMail MCP in Pydantic AI

Q: How do I list all email logs with Zoho ZeptoMail and Pydantic AI?

You call listlogs. Because you're using the Pydantic framework, you get a validated list of log objects. If the API sends back malformed data, your agent fails gracefully instead of corrupting your workflow.

Q: What is the best way to send messages with Zoho ZeptoMail and Pydantic AI?

Use sendtemplateemail if you have a fixed format. Use sendemail for one-off, unique communications. In either case, Pydantic validates all inputs (addresses, subjects, bodies) to ensure type safety.

Q: How does the MCP Server help verify sender domains for Zoho ZeptoMail and Pydantic AI?

The agent runs listdomains. This tool returns a list of verified domains. The Pydantic wrapper guarantees that the resulting data structure adheres exactly to what your code expects, eliminating guesswork.

Q: What if I need to check template availability?

You use listtemplates. This provides a structured list of all available templates. The tool output is instantly validated by Pydantic, so you don't have to worry about unexpected field names or types.

Q: If I run into issues, what data type is touched by this MCP Server?

This server deals with structured Email Log objects and a mix of String identifiers (for addresses, templates, domains). Pydantic ensures every field in these types is correctly typed at runtime.

Guarantee email data structure correctness using Pydantic AI.

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Setup Zoho ZeptoMail with Pydantic AI

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Send emails with guaranteed schema

The `send_email` tool allows your agent to send a custom message, but the response is validated against defined schemas. You pass the recipient and body content, knowing the structure of that data call will be correct. Similarly, when using `send_template_email`, Pydantic ensures the template ID and required parameters match expected types before execution, preventing runtime failures.

Validate email logs and status

Use `list_logs` to get a list of recent emails. The agent validates that every log entry returned includes mandatory fields like the unique ID and the timestamp. If data is missing, the agent fails loudly, telling you exactly what's wrong. For deep investigation, `get_log_details` retrieves specific information, all validated against expected JSON structures.

Verify sending infrastructure

The agent can validate your sender setup using the `list_domains` tool. This confirms that only valid and verified domains are being used as senders. Furthermore, calling `list_suppression_list` ensures you aren't attempting to contact a known bad address, making sure all data points for compliance are correct.

Setup guide

Set up Zoho ZeptoMail MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "zoho-zeptomail-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Zoho ZeptoMail tools.",
)

result = await agent.run("List recent Zoho ZeptoMail transactions")
print(result.output)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Zoho ZeptoMail. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Zoho ZeptoMail MCP in Pydantic AI

You call `list_logs`. Because you're using the Pydantic framework, you get a validated list of log objects. If the API sends back malformed data, your agent fails gracefully instead of corrupting your workflow.

Use `send_template_email` if you have a fixed format. Use `send_email` for one-off, unique communications. In either case, Pydantic validates all inputs (addresses, subjects, bodies) to ensure type safety.

The agent runs `list_domains`. This tool returns a list of verified domains. The Pydantic wrapper guarantees that the resulting data structure adheres exactly to what your code expects, eliminating guesswork.

You use `list_templates`. This provides a structured list of all available templates. The tool output is instantly validated by Pydantic, so you don't have to worry about unexpected field names or types.

This server deals with structured `Email Log` objects and a mix of `String` identifiers (for addresses, templates, domains). Pydantic ensures every field in these types is correctly typed at runtime.

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