How to Use the DigitalChalk MCP in CrewAI

Q: Can multiple agents in a CrewAI team share DigitalChalk tools?

Yes. You pass the server URL in the mcps list when defining your crew, allowing both research and action agents to use searchusersbyidentity dynamically across your DigitalChalk database.

Q: How do I restrict which DigitalChalk tools a CrewAI agent can use?

Use the MCP Server class from CrewAI to apply a toolfilter. You can limit your support agent to listuserenrollments while keeping DigitalChalk account metadata tools locked.

Q: Does CrewAI support sequential workflows for DigitalChalk administration?

Yes. One agent can extract a user profile using getuserlearningprofile, and the next agent in the sequence can analyze the data to recommend new courses via listcourseofferings.

Deploy specialized CrewAI agent teams to manage your DigitalChalk courses and track learner performance autonomously.

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Connect DigitalChalk MCP to CrewAI

Create your Vinkius account to connect DigitalChalk to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup DigitalChalk with CrewAI

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Run Multi-Agent Audits with this MCP Server

Let a crew of specialized agents run your academy. One CrewAI agent can query `list_lms_users` to find inactive profiles, while a moderator agent uses `list_user_enrollments` to check their DigitalChalk status. This MCP Server gives your entire team of agents shared access to the LMS. They coordinate actions in sequence, passing raw data from one tool to the next without human intervention.

Autonomous Academic Performance Monitoring

Set up a dedicated CrewAI grading agent to monitor exam results. The agent uses `list_assessment_exams` to retrieve the current test structures across all DigitalChalk courses. A second analyst agent can pull performance metrics using `list_high_performing_learners`. Together, they build a detailed picture of course difficulty and flag exams that might be too hard.

Automated Student Support and Outreach

Run your student support team on autopilot using CrewAI. When a student finishes a course, your agent detects it using `list_recent_course_completions` and triggers the next step in the DigitalChalk workflow. The outreach agent can then query `get_user_learning_profile` to see the student's full history. It writes a personalized email referencing their specific achievements without any manual copying.

Setup guide

Set up DigitalChalk MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke DigitalChalk tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="DigitalChalk Analyst",
    goal="Access and analyze DigitalChalk data via MCP.",
    backstory="Expert analyst with direct DigitalChalk access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent DigitalChalk transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="DigitalChalk Analyst",
        goal="Access and analyze DigitalChalk data via MCP.",
        backstory="Expert analyst with direct DigitalChalk access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent DigitalChalk transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DigitalChalk. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about DigitalChalk MCP in CrewAI

Yes. You pass the server URL in the `mcps` list when defining your crew, allowing both research and action agents to use `search_users_by_identity` dynamically across your DigitalChalk database.

Use the MCP Server class from CrewAI to apply a `tool_filter`. You can limit your support agent to `list_user_enrollments` while keeping DigitalChalk account metadata tools locked.

Yes. One agent can extract a user profile using `get_user_learning_profile`, and the next agent in the sequence can analyze the data to recommend new courses via `list_course_offerings`.

The crew connects via secure HTTP or SSE. Vinkius handles the transport layer, letting your agents focus on parsing the course settings from `get_offering_details`.

Nowhere on our end. Vinkius acts as an ephemeral MCP proxy inside a secure V8 isolate, meaning your sensitive learner profiles and quiz grades are passed directly to your CrewAI environment and never written to disk.

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