How to Use the Dovetail MCP in CrewAI

Deploy specialized research crews in CrewAI to autonomously manage and synthesize your qualitative data.

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Connect Dovetail MCP to CrewAI

Create your Vinkius account to connect Dovetail 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 Dovetail with CrewAI

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Perplexity

Autonomous research crews using CrewAI

Assign an agent to monitor `list_notes` while another focuses on `create_insight` for synthesis. CrewAI lets these agents share memory, so your research team can work in a sequence without manual intervention. This setup is for heavy-duty research operations. You set the goal, and the agents handle the data retrieval and categorization.

Role-based research operations

Create specialized agents that only have access to `list_projects` and `get_project_details`. This keeps your research operations organized by domain or project scope. By restricting tool usage, you ensure that your 'Research Analyst' agent doesn't accidentally mess with workspace settings while it is processing data.

Collaborative insight generation

Enable your crew to build a collective understanding of your research notes. Agents can pass data between each other to reach a consensus before committing an insight with `create_insight`. This is how you scale research. You build a pipeline that handles the raw data and outputs ready-to-use insights.

Setup guide

Set up Dovetail 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 Dovetail tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass the server URL to your agent definition in the mcps list. The framework will automatically register the available tools.

Yes, the agent crew shares memory during the execution phase. They can pull project details and apply them to ongoing research tasks.

The server supports the standard MCP transport protocols used by the framework. It works perfectly with hierarchical agent structures.

Use tool filters to limit which agent has access to write tools. This prevents runaway automation and keeps your API usage in check.

All communication is ephemeral and encrypted. The server does not persist your notes or participant quotes outside of your own workspace environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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