Metrc MCP Server for AutoGen 10 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Metrc as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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="metrc_agent",
tools=tools,
system_message=(
"You help users with Metrc. "
"10 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 Metrc MCP Server
Connect your Metrc account to any AI agent and take full control of your cannabis track-and-trace compliance through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Metrc tools. Connect 10 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
- Facility Oversight — List all licensed facilities and fetch detailed metadata for your operations
- Inventory Tracking — Retrieve active items, strains, and inventory packages with real-time status visibility
- Supply Chain Management — Monitor plant life cycles, harvest batches, and incoming inventory transfers securely
- Compliance Auditing — List active sales receipts and verify unit of measure configurations
- Detailed Inspection — Fetch comprehensive metadata for individual packages and state-specific license configurations
The Metrc MCP Server exposes 10 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.
How to Connect Metrc to AutoGen via MCP
Follow these steps to integrate the Metrc MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 10 tools from Metrc automatically
Why Use AutoGen with the Metrc MCP Server
AutoGen provides unique advantages when paired with Metrc through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Metrc tools to solve complex tasks
Role-based architecture lets you assign Metrc 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 Metrc tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Metrc tool responses in an isolated environment
Metrc + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Metrc MCP Server delivers measurable value.
Collaborative analysis: one agent queries Metrc while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Metrc, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Metrc data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Metrc responses in a sandboxed execution environment
Metrc MCP Tools for AutoGen (10)
These 10 tools become available when you connect Metrc to AutoGen via MCP:
get_package_details
Get details for a specific package
get_unit_of_measures
g. Grams, Ounces). List all units of measure
list_active_harvests
List active harvests for a facility
list_active_items
List active items for a facility
list_active_packages
List active packages for a facility
list_active_sales
List active sales receipts
list_active_strains
List active strains for a facility
list_facilities
List all licensed facilities
list_incoming_transfers
List incoming inventory transfers
list_tracked_plants
List tracked plants for a facility
Example Prompts for Metrc in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Metrc immediately.
"List all active facilities associated with my Metrc account."
"Show active inventory packages for license 'LIC-12345'."
"Get details for package label 'ABCDEFG1234567'."
Troubleshooting Metrc MCP Server with AutoGen
Common issues when connecting Metrc to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Metrc + AutoGen FAQ
Common questions about integrating Metrc MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
Connect Metrc with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Metrc to AutoGen
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.
