Can I block a fraudulent user through the agent?

Yes! Use the `apply_user_decision` tool with the user's ID and the appropriate decision ID (like `block_user`). The action will be applied in Sift immediately.

How do I check the risk score for a specific customer?

Use the `get_user_fraud_score` tool with the customer's unique ID. Your agent will fetch the latest risk score generated by Sift's machine learning models.

Where do I find my Sift API Key and Account ID?

Log in to your Sift Dashboard and navigate to **Settings -> API Keys**. You will find your REST API Key and Account ID there.

Sift (Chargeback) MCP Server for LangChain 8 tools — connect in under 2 minutes

Name: Sift (Chargeback)
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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({
        "sift-chargeback": {
            "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 Sift (Chargeback), show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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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 Sift (Chargeback) MCP Server

Connect your Sift account to any AI agent and take full control of your fraud protection and chargeback management through natural conversation. Streamline risk analysis and dispute resolution.

LangChain's ecosystem of 500+ components combines seamlessly with Sift (Chargeback) through native MCP adapters. Connect 8 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

Chargeback Reporting — Notify Sift of new chargeback events, including states and reasons natively
Fraud Intelligence — Retrieve real-time fraud scores for users to evaluate transaction risk flawlessly
Decision Automation — Apply manual or automated decisions (e.g., block user, accept order) securely
Dispute Oversight — List and audit the history of decisions and labels applied to any user flawlessly
Workflow Visibility — Access and monitor your configured fraud prevention workflows in real-time
Behavioral Tracking — Log custom events like logins or transactions to refine Sift's machine learning directly within your workspace

The Sift (Chargeback) MCP Server exposes 8 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.

How to Connect Sift (Chargeback) to LangChain via MCP

Follow these steps to integrate the Sift (Chargeback) MCP Server with LangChain.

Install dependencies

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

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 8 tools from Sift (Chargeback) via MCP

Why Use LangChain with the Sift (Chargeback) MCP Server

LangChain provides unique advantages when paired with Sift (Chargeback) through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Sift (Chargeback) MCP tools with 500+ LangChain components

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

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

Memory and conversation persistence let agents maintain context across Sift (Chargeback) queries for multi-turn workflows

Sift (Chargeback) + LangChain Use Cases

Practical scenarios where LangChain combined with the Sift (Chargeback) MCP Server delivers measurable value.

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

Autonomous research agents: LangChain agents query Sift (Chargeback), synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Sift (Chargeback) tools with web scrapers, databases, and calculators in a single agent run

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

Sift (Chargeback) MCP Tools for LangChain (8)

These 8 tools become available when you connect Sift (Chargeback) to LangChain via MCP:

apply_user_decision

Apply a manual decision to a user (e.g. block_user)

get_user_fraud_labels

Retrieve labels (e.g. $bad, $good) applied to a user

get_user_fraud_score

Get the current fraud score for a user

list_sift_decisions

List available decisions (actions) in Sift

list_sift_workflows

List configured fraud prevention workflows

list_user_decision_history

List the history of decisions applied to a user

report_sift_chargeback

Report a chargeback event to Sift

track_sift_event

Track a general event (e.g. $login, $transaction) in Sift

Example Prompts for Sift (Chargeback) in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Sift (Chargeback) immediately.

"What is the fraud score for user 'user_abc_123'?"

"Report a chargeback for order #999 from user 'user_789' as '$fraud'."

"Show me the last 5 decisions applied to user 'user_456'."

Troubleshooting Sift (Chargeback) MCP Server with LangChain

Common issues when connecting Sift (Chargeback) to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Sift (Chargeback) + LangChain FAQ

Common questions about integrating Sift (Chargeback) MCP Server with LangChain.

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.

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.