How do I get Insightly API credentials?

Log in to Insightly, click your profile icon, go to User Settings, and scroll down to the API Key section. You will also see your API URL which contains your pod (e.g., na1).

The pod is the region identifier in your Insightly API URL, such as 'na1' for North America or 'eu1' for Europe.

Can I see sales opportunities?

Yes, the list_opportunities tool provides access to all sales opportunities recorded in your Insightly account.

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

Name: Insightly
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 Insightly 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 Insightly "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

Fully ManagedVinkius Servers

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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 Insightly MCP Server

Empower your AI agents to manage your customer relationships with Insightly. This MCP server allows you to list and retrieve contacts, organizations, opportunities, and projects directly through the Insightly API. Ideal for automating sales workflows and project tracking within your CRM.

Pydantic AI validates every Insightly tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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.

The Insightly 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 Insightly to Pydantic AI via MCP

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

Why Use Pydantic AI with the Insightly MCP Server

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

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

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

Insightly + Pydantic AI Use Cases

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

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

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

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

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

Insightly MCP Tools for Pydantic AI (10)

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

get_contact

Retrieves details for a specific contact

list_contacts

Lists all contacts in Insightly

list_events

Lists all calendar events

list_leads

Lists all marketing leads

list_opportunities

Lists all sales opportunities

list_organisations

Lists all registered organisations

list_projects

Lists all active and past projects

list_tasks

Lists all tasks across projects

list_teams

Lists all defined teams

list_users

Lists all users in the system

Example Prompts for Insightly in Pydantic AI

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

"List all contacts in Insightly."

"Show me active projects in my Insightly account."

"Check for any new sales opportunities."

Troubleshooting Insightly MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Insightly + Pydantic AI FAQ

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