Cloverly MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Check Cloverly Status, Create Estimate, Create Purchase, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Cloverly 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 Cloverly app connector for LlamaIndex is a standout in the Data Analytics 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 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 Cloverly. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Cloverly?"
)
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 Cloverly MCP Server
Connect your Cloverly account to any AI agent and take full control of your sustainability initiatives and automated carbon management workflows through natural conversation.
LlamaIndex agents combine Cloverly tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Footprint Orchestration — Calculate real-time carbon footprint estimates for diverse activities including logistics (freight, shipping), travel (flights, vehicles), and energy usage programmatically
- Automated Offset Ingestion — Execute the purchase of carbon offsets based on specific activity estimates or fixed currency amounts to maintain high-fidelity sustainability compliance
- Project Intelligence — Access your complete directory of high-impact environmental projects (wind, solar, reforestation) to understand the source of your offsets directly through your agent
- Transaction Monitoring — Programmatically track your purchase history and retrieve detailed metadata, certificates, and receipts for operational and regulatory reporting
- Sustainability Visibility — Check the status of individual offset purchases and monitor account-level metadata to perfectly coordinate your organization's climate action
The Cloverly MCP Server exposes 12 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 12 Cloverly tools available for LlamaIndex
When LlamaIndex connects to Cloverly through Vinkius, your AI agent gets direct access to every tool listed below — spanning carbon-offsetting, sustainability, emissions-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.
Verify connectivity
Create a carbon estimate
Purchase carbon offsets
Get account info
Get estimate details
Get impact by type
Get impact summary
Get project details
Get purchase details
List estimates
List offset projects
List purchases
Connect Cloverly to LlamaIndex via MCP
Follow these steps to wire Cloverly 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 Cloverly MCP Server
LlamaIndex provides unique advantages when paired with Cloverly through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Cloverly tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Cloverly tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Cloverly, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Cloverly tools were called, what data was returned, and how it influenced the final answer
Cloverly + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Cloverly MCP Server delivers measurable value.
Hybrid search: combine Cloverly real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Cloverly 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 Cloverly for fresh data
Analytical workflows: chain Cloverly queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Cloverly in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Cloverly immediately.
"Calculate the carbon footprint for a 10kg shipment from Berlin to Paris."
"List the available reforestation projects on Cloverly."
"Show the status of my latest offset purchase 'pur_456'."
Troubleshooting Cloverly MCP Server with LlamaIndex
Common issues when connecting Cloverly to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCloverly + LlamaIndex FAQ
Common questions about integrating Cloverly MCP Server with LlamaIndex.