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 LangChain 10 tools — connect in under 2 minutes

Name: Insightly
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Insightly through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "insightly": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Insightly, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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Ed25519Audit chain

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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.

LangChain's ecosystem of 500+ components combines seamlessly with Insightly through native MCP adapters. Connect 10 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

The Insightly MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain 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 LangChain via MCP

Follow these steps to integrate the Insightly MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Insightly via MCP

Why Use LangChain with the Insightly MCP Server

LangChain provides unique advantages when paired with Insightly through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents — combine Insightly MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Insightly queries for multi-turn workflows

Insightly + LangChain Use Cases

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

RAG with live data: combine Insightly tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Insightly, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Insightly tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Insightly tool call, measure latency, and optimize your agent's performance

Insightly MCP Tools for LangChain (10)

These 10 tools become available when you connect Insightly to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Insightly + LangChain FAQ

Common questions about integrating Insightly MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.