Can I update stock for multiple products at once?

Yes! Use the `update_product_stock` tool. You can provide an array of SKU IDs and their new stock levels, and the agent will sync them across Channable.

How do I see orders from a specific marketplace like Amazon?

Use the `list_marketplace_orders` tool with your project ID. The agent will return all recent orders, and you can see the originating channel (e.g., Amazon, eBay) for each.

Where do I find my Channable API Token?

Log in to Channable, go to 'Company Settings' in the sidebar, and then select 'Channable API'. You can generate and copy your token from there.

Channable MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: Channable
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Channable through Vinkius, pass the Edge URL in the `mcps` parameter and every Channable 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="Channable Specialist",
    goal="Help users interact with Channable effectively",
    backstory=(
        "You are an expert at leveraging Channable 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 Channable "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

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

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DLPData protection

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Ed25519Audit chain

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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 Channable MCP Server

Connect your Channable account to any AI agent and orchestrate your marketplace order management and stock synchronization through natural conversation. Streamline how you sell across Amazon, eBay, bol.com, and more.

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

What you can do

Order Fulfillment — List and retrieve details for orders from all connected marketplaces natively
Stock Synchronization — Update product stock levels across all channels to prevent overselling flawlessly
Shipment Tracking — Update order statuses and send tracking information back to marketplaces securely
Returns Oversight — List and manage customer returns directly from your chat interface flawlessly
Project Visibility — Access and monitor multiple projects and connected channels in real-time
Commerce Intelligence — Retrieve detailed order metadata and project summaries directly within your workspace

The Channable MCP Server exposes 8 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 Channable to CrewAI via MCP

Follow these steps to integrate the Channable 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 8 tools from Channable

Why Use CrewAI with the Channable MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Channable 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

Channable + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Channable 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 Channable, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Channable 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 Channable against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Channable MCP Tools for CrewAI (8)

These 8 tools become available when you connect Channable to CrewAI via MCP:

get_order_details

Get detailed information for a specific order

get_project_summary

Get summary details for a specific project

list_channable_projects

List all projects for the company

list_connected_channels

List connected marketplace channels for a project

list_customer_returns

List customer returns for a specific project

list_marketplace_orders

List orders from connected marketplaces for a project

list_order_shipments

List shipments and tracking info for a project

update_product_stock

Update stock levels for products in a project

Example Prompts for Channable in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Channable immediately.

"Show me the last 10 orders from all marketplaces."

"Update stock for SKU 'TSHIRT-L-RED' to 25 units in project 123."

"List all active channels for project 456."

Troubleshooting Channable MCP Server with CrewAI

Common issues when connecting Channable 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.

Channable + CrewAI FAQ

Common questions about integrating Channable 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.