SkootEco MCP Server for LlamaIndexGive LlamaIndex instant access to 18 tools to Add Emission, Check Skooteco Status, Get Account, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add SkootEco as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The SkootEco app connector for LlamaIndex is a standout in the Security Compliance category — giving your AI agent 18 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to SkootEco. "
"You have 18 tools available."
),
)
response = await agent.run(
"What tools are available in SkootEco?"
)
print(response)
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 SkootEco MCP Server
Take control of your corporate sustainability targets by connecting SkootEco to your AI agents. With 18 specialized environmental tools, your AI can programmatically log emissions across all GHG scopes, purchase certified carbon offsets, track reforestation projects, and dynamically generate compliance reports.
LlamaIndex agents combine SkootEco tool responses with indexed documents for comprehensive, grounded answers. Connect 18 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Track direct and indirect emissions (GHG Scope 1, 2, 3)
- Automatically calculate supply chain carbon footprint
- Purchase certified carbon offset credits programmatically
- Fund reforestation projects and track your tree count
- Publish your public sustainability impact profile
- Generate CSRD and TCFD-aligned ESG reports
Who is it for?
Crucial for ESG managers, sustainability officers, and environmentally conscious businesses looking to accurately track, offset, and report on their carbon emissions.The SkootEco MCP Server exposes 18 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 18 SkootEco tools available for LlamaIndex
When LlamaIndex connects to SkootEco through Vinkius, your AI agent gets direct access to every tool listed below — spanning carbon-emissions, esg-reporting, sustainability, 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.
Log an emission
Verify connectivity
Get account info
Get total emissions
Get emissions by category
Get emissions by scope
Get ESG report
Get impact profile
Get impact metrics
Get offset details
Get project details
Get summary report
Get tree count
List emission categories
List carbon offsets
List climate projects
Plant a tree
Purchase carbon offset
Connect SkootEco to LlamaIndex via MCP
Follow these steps to wire SkootEco into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the SkootEco MCP Server
LlamaIndex provides unique advantages when paired with SkootEco through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine SkootEco tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain SkootEco tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query SkootEco, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what SkootEco tools were called, what data was returned, and how it influenced the final answer
SkootEco + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the SkootEco MCP Server delivers measurable value.
Hybrid search: combine SkootEco real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query SkootEco to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying SkootEco for fresh data
Analytical workflows: chain SkootEco queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for SkootEco in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with SkootEco immediately.
"Show my Scope 3 supply chain emissions in SkootEco."
"Plant 100 trees through SkootEco to offset our Q1 travel emissions."
"Generate our ESG compliance report from SkootEco for the board meeting."
Troubleshooting SkootEco MCP Server with LlamaIndex
Common issues when connecting SkootEco to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSkootEco + LlamaIndex FAQ
Common questions about integrating SkootEco MCP Server with LlamaIndex.