How to Use the Insightly MCP in AutoGen
Build consensus-driven AutoGen agent squads that debate and analyze Insightly sales pipelines.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Insightly MCP to AutoGen
Create your Vinkius account to connect Insightly to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Resolve CRM bottlenecks through AutoGen agent debates
The `list_leads` tool feeds raw Insightly marketing data into your AutoGen multi-agent system. One AutoGen agent analyzes lead quality while another flags operational risks, debating the best follow-up strategy before taking action on the Insightly lead. This cooperative AutoGen setup prevents hasty Insightly CRM decisions. By combining `list_opportunities` with structured AutoGen debates, your agents reach a consensus on which Insightly deals require immediate executive attention.
Audit project status with an MCP Server squad
This MCP Server provides the tools your AutoGen agents need to run complete operational audits on Insightly using `list_projects` and `list_tasks`. A dedicated AutoGen PM agent tracks deadlines while a resource agent checks team availability against Insightly schedules. Your AutoGen agents cross-reference their findings using `list_teams` and `list_users` to map Insightly dependencies. If an Insightly task is lagging, the AutoGen agents negotiate a reassignment plan based on actual workload data.
Coordinate team events and organization mapping
The `list_events` tool allows your AutoGen scheduling agents to coordinate meetings based on actual Insightly calendar data. Your AutoGen squad looks up company structures using `list_organisations` to ensure the correct Insightly stakeholders are invited. Your AutoGen agents use `get_contact` and `list_contacts` to build complete Insightly org charts during their discussions. Your AutoGen agents verify details internally before presenting a finalized Insightly meeting agenda to you.
Set up Insightly MCP in AutoGen
Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]package - Active Vinkius subscription with a valid endpoint token
- 1
Install AutoGen with MCP
Run
pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includesmcp_server_toolsfor stateless tool access. - 2
Fetch tools from the MCP
Call
mcp_server_tools(SseServerParams(url=...))with your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Run your agent
Pass the tools to
AssistantAgentand callagent.run(). The agent invokes Insightly tools and returns structured results.
from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
tools = await mcp_server_tools(server_params)
agent = AssistantAgent(
name="Insightly_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Insightly data")
print(result.messages[-1].content) Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]+autogen-agentchat - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Same packages as above.
McpWorkbenchis ideal when your agent needs stateful sessions across multiple tool calls. - 2
Use McpWorkbench as context manager
Wrap your agent in
async with McpWorkbench(...)to maintain shared state and resources. The workbench manages the full MCP session lifecycle. - 3
Run with workbench
Pass
workbench=workbenchto your agent. State is preserved across multiple tool calls within the same session.
from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
async with McpWorkbench(server_params) as workbench:
agent = AssistantAgent(
name="Insightly_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Insightly data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Insightly. 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.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Insightly MCP in AutoGen
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
Start using the Insightly MCP today
We host it, we monitor it, we maintain it. You just paste one token.