Redo MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Redo 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 Redo. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Redo?"
)
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 Redo MCP Server
Connect your Redo account to any AI agent to automate your returns management and shipping protection workflows through the Model Context Protocol (MCP). Redo provides a comprehensive suite for handling customer returns, exchanges, and package protection claims for lost or damaged items. This MCP server enables you to track return requests, approve claims, and process final resolutions directly through natural conversation.
LlamaIndex agents combine Redo 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.
Key Features
- Returns & Claims Oversight — List all return requests and shipping protection claims, checking their status and customer metadata instantly.
- Status Automation — Update the lifecycle status of a return (e.g., approved, rejected) programmatically from your chat interface.
- Resolution Processing — Trigger final actions like refunds, store credits, or exchange order creation for lost or damaged packages.
- Collaborative Notes — Add internal comments and communication logs to any return or claim record for better team alignment.
- Coverage Discovery — Access high-level information about your shipping protection settings and eligible products.
- Shipping Rate Calculation — Retrieve real-time shipping rates for return packages to estimate costs for your customers.
- Webhook Visibility — Monitor active webhooks to ensure your internal systems are receiving real-time return notifications.
- Real-time Synchronization — Keep your post-purchase operations accessible to your AI assistant without leaving your primary workspace.
The Redo 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.
How to Connect Redo to LlamaIndex via MCP
Follow these steps to integrate the Redo 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 12 tools from Redo
Why Use LlamaIndex with the Redo MCP Server
LlamaIndex provides unique advantages when paired with Redo through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Redo tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Redo tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Redo, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Redo tools were called, what data was returned, and how it influenced the final answer
Redo + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Redo MCP Server delivers measurable value.
Hybrid search: combine Redo real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Redo 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 Redo for fresh data
Analytical workflows: chain Redo queries with LlamaIndex's data connectors to build multi-source analytical reports
Redo MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Redo to LlamaIndex via MCP:
add_internal_note
Post a return comment
approve_return_claim
Approve a request
get_protection_summary
Get coverage details
get_return_details
Get return metadata
get_return_shipping_rates
Get shipping costs
get_store_details
Get store metadata
list_protected_items
List covered products
list_return_webhooks
List webhook configs
list_store_returns
List returns/claims
process_final_resolution
Finalize return/claim
reject_return_claim
Reject a request
verify_api_connection
Check connection
Example Prompts for Redo in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Redo immediately.
"List the last 5 pending return requests."
"Approve the return claim for ID 'ret_abc123'."
"Get the shipping rates for return 'ret_abc123'."
Troubleshooting Redo MCP Server with LlamaIndex
Common issues when connecting Redo to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpRedo + LlamaIndex FAQ
Common questions about integrating Redo 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 Redo 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 Redo to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.