How to Use the CallGear MCP in CrewAI

Q: How do I connect CrewAI to my CallGear workspace?

Pass your Vinkius HTTP endpoint directly into the agent's mcps array parameter. The MCP protocol automatically discovers the available tools and assigns them to the agent.

Q: Can multiple CrewAI agents share the same CallGear tools?

Yes. You can give your analyst agent access to getcallsreport while your manager agent uses listusers to assign follow-ups.

Q: Can I limit which CallGear tools a specific MCP agent can access?

Yes. Use the MCPServerHTTP class from crewai.mcp and apply a toolfilter to ensure your junior agents only see read-only tools like listtags.

Deploy a coordinated crew of specialized AI agents to analyze your CallGear campaign performance and call logs.

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Connect CallGear MCP to CrewAI

Create your Vinkius account to connect CallGear 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 CallGear with CrewAI

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Run multi-agent marketing audits using this MCP Server

Assign one agent to analyze traffic via `list_traffic_sources` while a conversion agent queries `get_calls_report` to find matching leads. They share memory to correlate which ad channels drive actual phone conversations. This setup turns raw marketing metrics into a collaborative research task without manual exporting.

Autonomous campaign monitoring and alerting

Let a specialized moderator agent watch your active marketing efforts by using `list_ad_campaigns` to get a list of active campaigns. If performance metrics drop below your targets, a separate notification agent can pull account details via `get_account_info` to identify who to contact. The entire loop runs without human intervention.

Collaborative communication performance analysis

Analyze your team's overall phone and chat performance by calling `get_communications_report` and `get_site_daily_stats` to build a complete view of customer touchpoints. A second agent can pull routing details using `list_call_scenarios` to suggest optimizations. The agents work sequentially, passing findings down the chain to build a final recommendation report.

Setup guide

Set up CallGear 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 CallGear tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent CallGear 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 CallGear. 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 CallGear MCP in CrewAI

Pass your Vinkius HTTP endpoint directly into the agent's `mcps` array parameter. The MCP protocol automatically discovers the available tools and assigns them to the agent.

Yes. You can give your analyst agent access to `get_calls_report` while your manager agent uses `list_users` to assign follow-ups.

Agents use their shared memory to pass summarized insights rather than raw payloads. An agent can query `get_communications_report` and hand a clean summary to the next agent in the sequence.

Yes. Use the `MCPServerHTTP` class from `crewai.mcp` and apply a `tool_filter` to ensure your junior agents only see read-only tools like `list_tags`.

Your customer phone logs and chat histories are never stored by Vinkius. Every connection uses ephemeral, zero-trust MCP sandboxes to guarantee that sensitive interaction data remains private.

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