Cedar AI MCP Server for AutoGenGive AutoGen instant access to 12 tools to Arrive Train, Depart Train, Get Railcar Details, and more
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Cedar AI as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
Ask AI about this App Connector for AutoGen
The Cedar AI app connector for AutoGen is a standout in the Erp Operations category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="cedar_ai_agent",
tools=tools,
system_message=(
"You help users with Cedar AI. "
"12 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
asyncio.run(main())
* 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 Cedar AI MCP Server
Connect your Cedar AI railway management account to any AI agent and simplify how you coordinate rail operations, track car movements, and manage logistics documentation through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Cedar AI tools. Connect 12 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Inventory Management — List all railcars currently in your facility and retrieve detailed metadata and status for individual units.
- Car Movement Tracking — Record placements (setouts) and removals (pickups) of railcars at specific locations or tracks.
- Logistics Documentation — List and query waybills to understand shipping instructions, routes, and commodity data.
- Work Order Control — Manage the lifecycle of movement instructions by listing and updating work orders and associated tasks.
- Consist Coordination — Record train arrivals and departures to keep your inventory and operations synchronized.
- Status Maintenance — Update railcar tags and conditions (e.g., Bad Order, Empty/Loaded) directly via AI commands.
The Cedar AI MCP Server exposes 12 tools through the Vinkius. Connect it to AutoGen in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 Cedar AI tools available for AutoGen
When AutoGen connects to Cedar AI through Vinkius, your AI agent gets direct access to every tool listed below — spanning railway-management, logistics-optimization, freight-tracking, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Record train arrival
Record train departure
Get details for a specific railcar
Get details for a specific waybill
Get details for a specific work order
List railcars currently in inventory
List waybills
List work orders
Record removal of cars
Record placement of cars
g., Bad Order, Clean, Loaded/Empty). Update status of a railcar
Update a work order
Connect Cedar AI to AutoGen via MCP
Follow these steps to wire Cedar AI into AutoGen. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install AutoGen
pip install "autogen-ext[mcp]"Replace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenIntegrate into workflow
Explore tools
Why Use AutoGen with the Cedar AI MCP Server
AutoGen provides unique advantages when paired with Cedar AI through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Cedar AI tools to solve complex tasks
Role-based architecture lets you assign Cedar AI tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Cedar AI tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Cedar AI tool responses in an isolated environment
Cedar AI + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Cedar AI MCP Server delivers measurable value.
Collaborative analysis: one agent queries Cedar AI while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Cedar AI, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Cedar AI data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Cedar AI responses in a sandboxed execution environment
Example Prompts for Cedar AI in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Cedar AI immediately.
"List all railcars currently in the main yard inventory."
"Record a setout of cars 'TBOX 101, TBOX 102' at 'Customer Track 4'."
"Show me the details for waybill 'WB-88231'."
Troubleshooting Cedar AI MCP Server with AutoGen
Common issues when connecting Cedar AI to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Cedar AI + AutoGen FAQ
Common questions about integrating Cedar AI MCP Server with AutoGen.