How to Use the Bland AI MCP in CrewAI

Q: How do I filter Bland AI tools for specific CrewAI agents?

Use the toolfilter option in your agent config. This ensures your research agents don't accidentally start calling customers.

Deploy autonomous phone agent crews using CrewAI and this MCP Server.

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Connect Bland AI MCP to CrewAI

Create your Vinkius account to connect Bland AI 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 Bland AI with CrewAI

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Coordinate phone crews in CrewAI

Assign `send_call` to your lead agent and `get_transcript` to your analyst agent. They work together to manage the entire lifecycle of your phone operations. The agents share memory, so the analyst knows exactly which call the leader just initiated.

Autonomous call management in CrewAI

Let your monitor agent watch for active calls using `list_calls`. If a call runs too long, the monitor can trigger `stop_call` to save you money. This takes the manual labor out of your operations. Your crew handles the monitoring while you watch the results.

Dynamic pathway selection in CrewAI

Use `list_pathways` to let your agents decide which conversation flow to use. It allows your crew to adapt to different customer scenarios on the fly. The agents evaluate the context and pick the best pathway for the situation. It makes your phone presence smarter.

Setup guide

Set up Bland AI 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 Bland AI tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Include the server URL in your agent definition. CrewAI automatically pulls the tools so your crew can start making calls immediately.

Yes, you can give each agent in your crew specific access to different tools. One agent can handle calls while another manages the transcript database.

It is built for that. Your agents can monitor call logs and react without you typing a single command.

Use the tool_filter option in your agent config. This ensures your research agents don't accidentally start calling customers.

We isolate your call data behind a single authenticated endpoint. Your CrewAI agents operate within this secure boundary, preventing any unauthorized access to your records.

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