How to Use the Gamma (AI Presentations) MCP in CrewAI

Q: How do I add Gamma (AI Presentations) to a CrewAI agent?

Pass the server URL directly into the mcps array when defining your agent. For granular control, import MCPServerHTTP and use a toolfilter to restrict access.

Equip your CrewAI agents to autonomously draft, edit, and manage presentations.

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Connect Gamma (AI Presentations) MCP to CrewAI

Create your Vinkius account to connect Gamma (AI Presentations) 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 Gamma (AI Presentations) with CrewAI

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Perplexity

Autonomous slide drafting for researcher agents

`create_gamma` lets your presentation agent turn raw research into structured slide decks. While your analyst agent gathers data, the designer agent takes those findings and generates the document. They work in parallel. The output is immediate. Instead of handing off a text summary to a human, the crew delivers a polished, ready-to-present file. The entire process runs sequentially without manual formatting.

Workspace auditing with CrewAI

`list_gammas` lets a manager agent audit the entire workspace inventory. It maps out every existing presentation, document, and webpage. The agent reads the directory and determines what needs updating. For deep context, the agent uses `get_gamma` to read specific file contents. If a deck contains outdated metrics, the manager agent flags it and assigns an update task to a worker agent.

Self-correcting edits via MCP Server

`update_gamma` gives your crew the ability to revise decks based on feedback loops. A reviewer agent can critique a newly generated presentation, and the creator agent will execute the necessary edits. The crew iterates until the document meets your quality threshold. Sometimes drafts are too far gone. When that happens, the crew uses `delete_gamma` to scrap the file entirely. They clean up their own failed attempts before starting fresh.

Setup guide

Set up Gamma (AI Presentations) 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 Gamma (AI Presentations) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Gamma (AI Presentations) 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 Gamma. 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 Gamma (AI Presentations) MCP in CrewAI

Pass the server URL directly into the `mcps` array when defining your agent. For granular control, import `MCPServerHTTP` and use a `tool_filter` to restrict access.

Yes. You can give the creation tool to a designer agent and the deletion tool to a manager agent. Role-based access keeps your crew organized.

It depends on your setup. If you run hierarchical execution, a manager agent can evaluate the updated deck. If the edit failed, it will instruct the worker to try again.

You connect via standard HTTP or SSE transports. The CrewAI framework handles the routing, meaning your local scripts can drive remote server actions safely.

Vinkius isolates every session. When your crew reads presentation text or modifies slide structures, that data lives in a temporary V8 sandbox. The environment is destroyed the moment the agent finishes its task.

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