Greenspark MCP Server for AutoGen 12 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Greenspark 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="greenspark_agent",
tools=tools,
system_message=(
"You help users with Greenspark. "
"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 Greenspark MCP Server
Connect your Greenspark account to any AI agent and automate your business's environmental impact. Use natural language to trigger verified climate actions like planting trees or rescuing ocean plastic, and monitor your total sustainability goals in real-time.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Greenspark 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
- Impact Orchestration — Trigger new climate impacts programmatically by passing specific event data and quantities natively
- Live Tracking — Retrieve detailed impact records and summary reports to analyze your total environmental contribution flawlessly
- Project Discovery — List and explore the vetted environmental projects your contributions support globally
- Emission Estimation — Calculate the carbon footprint of transactions based on merchant categories to automate offsetting synchronously
- Asset Management — List and manage available impact badges and widgets to showcase your verified impact natively
- Webhook Integration — Configure and audit API webhooks to keep your internal systems synchronized with project updates flawlessly
The Greenspark 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.
How to Connect Greenspark to AutoGen via MCP
Follow these steps to integrate the Greenspark 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 12 tools from Greenspark automatically
Why Use AutoGen with the Greenspark MCP Server
AutoGen provides unique advantages when paired with Greenspark through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Greenspark tools to solve complex tasks
Role-based architecture lets you assign Greenspark 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 Greenspark tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Greenspark tool responses in an isolated environment
Greenspark + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Greenspark MCP Server delivers measurable value.
Collaborative analysis: one agent queries Greenspark while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Greenspark, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Greenspark data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Greenspark responses in a sandboxed execution environment
Greenspark MCP Tools for AutoGen (12)
These 12 tools become available when you connect Greenspark to AutoGen via MCP:
create_impact
Trigger a new climate impact (e.g. plant a tree)
create_webhook
Configure a new API webhook
estimate_footprint
Calculate the carbon footprint of a transaction
get_impact
Get details for a specific impact record
get_impact_summary
Get total aggregated impact data for the account
get_project
Get details for a specific environmental project
get_subscription
Get details of the account Greenspark subscription
list_badges
List available impact badges and widgets
list_impact_types
List available types of climate impact
list_impacts
List historical climate impacts generated
list_projects
List environmental projects supported by Greenspark
list_webhooks
List configured API webhooks
Example Prompts for Greenspark in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Greenspark immediately.
"Show my total climate impact summary"
"Plant 10 trees for our latest customer sale"
"Estimate the carbon footprint of a $50 flight purchase"
Troubleshooting Greenspark MCP Server with AutoGen
Common issues when connecting Greenspark to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Greenspark + AutoGen FAQ
Common questions about integrating Greenspark 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 Greenspark with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Google's framework for building production AI agents.
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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 Greenspark to AutoGen
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.
