Sift (Chargeback) MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Sift (Chargeback) as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
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 Sift (Chargeback). "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Sift (Chargeback)?"
)
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 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.
LlamaIndex agents combine Sift (Chargeback) tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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
- 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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Sift (Chargeback) MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 8 tools from Sift (Chargeback)
Why Use LlamaIndex with the Sift (Chargeback) MCP Server
LlamaIndex provides unique advantages when paired with Sift (Chargeback) through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Sift (Chargeback) tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Sift (Chargeback) tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Sift (Chargeback), a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Sift (Chargeback) tools were called, what data was returned, and how it influenced the final answer
Sift (Chargeback) + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Sift (Chargeback) MCP Server delivers measurable value.
Hybrid search: combine Sift (Chargeback) real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Sift (Chargeback) 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 Sift (Chargeback) for fresh data
Analytical workflows: chain Sift (Chargeback) queries with LlamaIndex's data connectors to build multi-source analytical reports
Sift (Chargeback) MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Sift (Chargeback) to LlamaIndex 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, $transaction) in Sift
Example Prompts for Sift (Chargeback) in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Sift (Chargeback) immediately.
"What is the fraud score for user 'user_abc_123'?"
"Report a chargeback for order #999 from user 'user_789' as '$fraud'."
"Show me the last 5 decisions applied to user 'user_456'."
Troubleshooting Sift (Chargeback) MCP Server with LlamaIndex
Common issues when connecting Sift (Chargeback) to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSift (Chargeback) + LlamaIndex FAQ
Common questions about integrating Sift (Chargeback) MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Sift (Chargeback) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
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 Sift (Chargeback) to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.