How to Use the Glama MCP in CrewAI

Q: How do I register Glama MCP tools with a CrewAI agent?

Pass the Vinkius HTTP URL directly into the mcps list of your agent. Your agent will automatically get access to tools like glamalistmcpservers and glamarungatewaychat.

Q: Can multiple CrewAI agents share the same Glama proxy?

Yes. You can configure a single instance of glamarungatewaychat and share it across your entire crew. This ensures all agents route their queries through the same managed gateway.

Q: How does CrewAI handle tool installation details from a Glama MCP Server?

The manager agent calls glamagetmcpserverinfo to read the setup requirements. It then uses these parameters to configure the runtime environment before invoking the tool.

Q: Can CrewAI agents access private Glama instances?

Yes. By calling glamagethostedinstances, your coordinator agent can list all private servers assigned to your account and delegate tasks to them.

Q: How does Glama protect private credentials and telemetry data in CrewAI?

The glamasendtelemetry tool only records execution duration and tool name metrics. All sensitive credentials, like your Vinkius API keys, remain inside the secure, ephemeral sandbox.

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Connect Glama MCP to CrewAI

Create your Vinkius account to connect Glama 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 Glama with CrewAI

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Multi-Agent Tool Sourcing in CrewAI

`glama_list_mcp_servers` allows your researcher agent to find specialized tools on the fly when standard tools cannot solve a task. The agent searches the global registry and passes the connection parameters to its peers. CrewAI handles the shared memory updates. Once the researcher finds the tool, the manager agent can assign it to a writer or analyst agent to execute the job.

Hierarchical Model Routing

`glama_run_gateway_chat` proxies prompts from different agents through a single endpoint to optimize API usage across your entire crew. Your supervisor agent can route complex tasks to high-tier models while leaving simple tasks on smaller models. This MCP Server prevents API key clutter across your Python environment. You configure the gateway once, and every agent in the crew uses it for isolated execution.

Dynamic Environmental Auditing

`glama_get_mcp_server_info` extracts the installation parameters and schema requirements for any server in the directory. Your moderator agent inspects these details to ensure the target server complies with crew rules. If the server requires unsupported environment variables, the moderator agent flags it. This keeps your automated pipelines from stalling due to missing configuration settings.

Setup guide

Set up Glama 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 Glama tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass the Vinkius HTTP URL directly into the `mcps` list of your agent. Your agent will automatically get access to tools like `glama_list_mcp_servers` and `glama_run_gateway_chat`.

Yes. You can configure a single instance of `glama_run_gateway_chat` and share it across your entire crew. This ensures all agents route their queries through the same managed gateway.

The manager agent calls `glama_get_mcp_server_info` to read the setup requirements. It then uses these parameters to configure the runtime environment before invoking the tool.

Yes. By calling `glama_get_hosted_instances`, your coordinator agent can list all private servers assigned to your account and delegate tasks to them.

The `glama_send_telemetry` tool only records execution duration and tool name metrics. All sensitive credentials, like your Vinkius API keys, remain inside the secure, ephemeral sandbox.

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