How to Use the Dynamo Software MCP in CrewAI

Q: How do I pass the Dynamo Software MCP Server to a CrewAI agent?

You can pass the server URL directly into the agent's mcps parameter during initialization. The framework automatically discovers the tools and makes them available to your specialized crew.

Q: Can I restrict which Dynamo Software MCP Server tools a specific CrewAI agent can use?

Yes, use the MCPServerHTTP class with a toolfilter to limit tool exposure. This ensures your research agent can only run listinvestmentfunds while keeping audit tools restricted.

Q: How do I monitor API usage across my multi-agent crew?

Have your lead agent call getdynamoaccountmetadata at the start of the task. This gives the crew visibility into your remaining API allocation so they can pace their queries.

Deploy a collaborative team of specialized investment agents using CrewAI and our Dynamo Software MCP Server.

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Create your Vinkius account to connect Dynamo Software 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 Dynamo Software with CrewAI

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Multi-Agent Audits via MCP Server

Audit your holdings with a specialized crew running `quick_portfolio_valuation_audit` to pull instant metrics. Your research agent can run this tool to get a snapshot of your holdings. A separate analyst agent then takes that data and runs `list_high_valuation_funds` to identify assets that need close attention. This cooperative approach mimics a human analyst team but operates in seconds.

Autonomous Investor Relations Monitoring

Track investor interactions autonomously with a crew running `list_latest_dynamo_activities` to monitor updates. When a monitoring agent spots a new lead, it coordinates with the rest of the crew. A second agent uses `list_active_investors_only` to confirm their funding status. The crew coordinates these checks autonomously, updating your CRM without manual data entry.

Intelligence-Driven Fund Research

Scout investment opportunities using a research crew running `search_investment_funds` to match your criteria. This allows your agents to filter through massive lists based on specific parameters. A second agent then calls `get_fund_details` to pull deep performance metrics on those matches. The crew synthesizes this data into a single report, saving your team hours of manual research.

Setup guide

Set up Dynamo Software 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 Dynamo Software tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You can pass the server URL directly into the agent's `mcps` parameter during initialization. The framework automatically discovers the tools and makes them available to your specialized crew.

Yes, use the `MCPServerHTTP` class with a `tool_filter` to limit tool exposure. This ensures your research agent can only run `list_investment_funds` while keeping audit tools restricted.

The crew uses shared memory to pass tool outputs between agents. For example, the output of `list_dynamo_portfolios` is automatically formatted and handed off to the analyzing agent for the next step.

Have your lead agent call `get_dynamo_account_metadata` at the start of the task. This gives the crew visibility into your remaining API allocation so they can pace their queries.

Yes, all data transfers are executed locally or through encrypted tunnels, ensuring your LP data never leaks. The server environment uses ephemeral runtimes that wipe all memory caches as soon as the crew finishes its run.

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