3,400+ MCP servers ready to use
Vinkius

Cloverly MCP Server for LangChainGive LangChain instant access to 12 tools to Check Cloverly Status, Create Estimate, Create Purchase, and more

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Cloverly through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Ask AI about this App Connector for LangChain

The Cloverly app connector for LangChain 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

python
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "cloverly": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Cloverly, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Cloverly
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

LangChain's ecosystem of 500+ components combines seamlessly with Cloverly through native MCP adapters. Connect 12 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain

When LangChain 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.

check_cloverly_status

Verify connectivity

create_estimate

Create a carbon estimate

create_purchase

Purchase carbon offsets

get_account

Get account info

get_estimate

Get estimate details

get_impact_by_type

Get impact by type

get_impact_summary

Get impact summary

get_project

Get project details

get_purchase

Get purchase details

list_estimates

List estimates

list_projects

List offset projects

list_purchases

List purchases

Connect Cloverly to LangChain via MCP

Follow these steps to wire Cloverly into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 12 tools from Cloverly via MCP

Why Use LangChain with the Cloverly MCP Server

LangChain provides unique advantages when paired with Cloverly through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents. combine Cloverly MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across Cloverly queries for multi-turn workflows

Cloverly + LangChain Use Cases

Practical scenarios where LangChain combined with the Cloverly MCP Server delivers measurable value.

01

RAG with live data: combine Cloverly tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query Cloverly, synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain Cloverly tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every Cloverly tool call, measure latency, and optimize your agent's performance

Example Prompts for Cloverly in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Cloverly immediately.

01

"Calculate the carbon footprint for a 10kg shipment from Berlin to Paris."

02

"List the available reforestation projects on Cloverly."

03

"Show the status of my latest offset purchase 'pur_456'."

Troubleshooting Cloverly MCP Server with LangChain

Common issues when connecting Cloverly to LangChain through the Vinkius, and how to resolve them.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Cloverly + LangChain FAQ

Common questions about integrating Cloverly MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.