How do I get my API Secret for Redo?

Log in to your Redo dashboard, navigate to Settings > API, and you can generate or copy your active secret key.

Are shipping protection claims handled differently than returns?

No, Redo treats shipping protection claims (for lost, damaged, or stolen items) as a specific type of return record, accessible via the same tools.

Can I approve a return request directly through the agent?

Yes! Use the 'approve_return_claim' tool and provide the Return ID. The agent will update the status in Redo instantly.

How do I see the reasons why customers are returning items?

The 'get_return_details' tool retrieves the full metadata for any request, which includes the specific return reason code and customer comments.

Redo MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Redo
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Redo through Vinkius, pass the Edge URL in the `mcps` parameter and every Redo tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Redo Specialist",
    goal="Help users interact with Redo effectively",
    backstory=(
        "You are an expert at leveraging Redo tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Redo "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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 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.

When paired with CrewAI, Redo becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Redo tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Redo MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from Redo

Why Use CrewAI with the Redo MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Redo through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Redo + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Redo MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Redo for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Redo, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Redo tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Redo against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Redo MCP Tools for CrewAI (12)

These 12 tools become available when you connect Redo to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

Common issues when connecting Redo to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Redo + CrewAI FAQ

Common questions about integrating Redo MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.