How to Use the Innform MCP in CrewAI

Q: How do I limit Innform tools for a specific CrewAI agent?

Use the toolfilter feature in your agent definition. This ensures your research agent only sees the tools it actually needs to perform its job.

Deploy a specialized CrewAI team to monitor learner progress and handle compliance escalations automatically.

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Connect Innform MCP to CrewAI

Create your Vinkius account to connect Innform 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 Innform with CrewAI

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Perplexity

Role-based learner monitoring

Assign a dedicated agent to monitor `list_results` for incomplete training. If a deadline passes, the agent can escalate the issue to a manager. Your crew specializes in different tasks like research, analysis, and reporting. This allows for a hierarchical response to compliance gaps.

Automated organizational reporting

Use your agents to fetch `list_departments` and `list_locations` to aggregate training stats. Your crew compiles these into a summary for your team. This removes the burden of manual reporting from your staff. The agents gather the data, clean it, and present the final numbers.

Dynamic pathway management

Query `list_pathways` to see which courses are assigned to specific groups. Your agents can suggest updates to training plans based on real-time completion data. It turns your static training catalog into a living system. Your crew ensures that every learner has the right modules assigned to them.

Setup guide

Set up Innform 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 Innform tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Innform 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="Innform Analyst",
        goal="Access and analyze Innform data via MCP.",
        backstory="Expert analyst with direct Innform access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Innform 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 Innform. 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.

Why Choose Vinkius

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Common questions about Innform MCP in CrewAI

Use the tool_filter feature in your agent definition. This ensures your research agent only sees the tools it actually needs to perform its job.

Agents share memory by default. Once one agent retrieves data, the rest of the crew can access that information to inform their next steps.

Yes, the server provides a clean interface for agents to call functions. It works perfectly with sequential or hierarchical crew structures.

You can throttle your agent's execution speed to match the API limits. This prevents your crew from overwhelming the system during high-load periods.

All requests are scoped to the specific agent task. The system enforces strict access control, ensuring no agent sees data beyond its assigned role.

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