How to Use the GlassFrog MCP in CrewAI

Q: How do I limit GlassFrog access for specific CrewAI agents?

Use the toolfilter parameter in your MCP setup. You can give your moderator agent full access while restricting your researcher agent to read-only tools.

Deploy a specialized agent crew to manage your organizational structure with GlassFrog.

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Connect GlassFrog MCP to CrewAI

Create your Vinkius account to connect GlassFrog 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 GlassFrog with CrewAI

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Claude

Perplexity

Autonomous tactical project management

Assign a project manager agent to monitor `list_tactical_projects` and update status items. It can identify stale projects and alert the team lead. This removes the manual burden of project hygiene. Your crew keeps the workspace clean without you lifting a finger.

Policy-aware research agents

Task a researcher agent with running `list_circle_policies` to provide context for your strategy sessions. It learns the constraints of your circle before making recommendations. This ensures every suggestion aligns with your existing rules. The agent reads the policy so you don't have to.

Checklist automation

Use an agent to run `list_checklist_items` across multiple circles to track progress on recurring tasks. The agent aggregates the data and reports back on completion rates. It turns raw lists into actionable insights. Your crew does the heavy lifting of tracking task completion.

Setup guide

Set up GlassFrog 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 GlassFrog tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Yes. CrewAI uses shared memory, so when one agent fetches role data, the rest of the team can use it for their tasks.

Use the tool_filter parameter in your MCP setup. You can give your moderator agent full access while restricting your researcher agent to read-only tools.

All data sent to your agents is encrypted in transit. We only expose the specific record details needed for the task, keeping your organizational directory private.

Yes. You just provide the Vinkius URL in your agent configuration. It works over standard transports like SSE or HTTP.

The server exposes your Holacracy metadata, including role definitions, circle metrics, and project lists. This is strictly read-only or write-restricted based on your configuration.

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