Knorish MCP Server for CrewAIGive CrewAI instant access to 12 tools to Create User, Create Webhook, Enroll User, and more

Name: Knorish
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The Knorish MCP Server for CrewAI is a standout in the Ecommerce category — giving your AI agent 12 tools to work with, ready to go from day one.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Knorish Specialist",
    goal="Help users interact with Knorish effectively",
    backstory=(
        "You are an expert at leveraging Knorish 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 Knorish "
        "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)

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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 Knorish MCP Server

Connect your Knorish account to any AI agent and manage your online course business through natural conversation.

When paired with CrewAI, Knorish becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Knorish 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

Course Management — List courses, inspect curricula, and track enrollment numbers
Student Tracking — Browse students with progress, completion rates, and engagement
Enrollment Monitoring — Track new enrollments, active students, and drop-offs
Content Browsing — Navigate course modules, lessons, and media content
Sales Analytics — Monitor revenue, orders, and conversion metrics
Certificate Management — Track certificate issuance and completion records

The Knorish MCP Server exposes 12 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 Knorish tools available for CrewAI

When CrewAI connects to Knorish through Vinkius, your AI agent gets direct access to every tool listed below — spanning online-courses, lms, student-tracking, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Create user on Knorish

Create a new user

create

Create webhook on Knorish

Create a new webhook

enroll

Enroll user on Knorish

Enroll a user in a course

get

Get account info on Knorish

Get academy account details

get

Get course on Knorish

Get course details

get

Get student progress on Knorish

Get student progress

get

Get user on Knorish

Get user details

list

List bundles on Knorish

List course bundles

list

List courses on Knorish

List all courses

list

List users on Knorish

List all users

list

List webhooks on Knorish

List webhooks

unenroll

Unenroll user on Knorish

Unenroll a user from a course

Connect Knorish to CrewAI via MCP

Follow these steps to wire Knorish into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 Knorish

Why Use CrewAI with the Knorish MCP Server

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

Knorish + CrewAI Use Cases

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

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

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

Example Prompts for Knorish in CrewAI

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

"Show all courses with enrollment numbers and the top-performing course."

"Show student progress for the Digital Marketing course and recent enrollments."

"Show the curriculum of the Python course and sales for this month."

Troubleshooting Knorish MCP Server with CrewAI

Common issues when connecting Knorish to CrewAI through 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.

Knorish + CrewAI FAQ

Common questions about integrating Knorish 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.

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