How to Use the Glean MCP in CrewAI

Q: How do I assign Glean tools to specific agents in CrewAI?

You pass the MCP Server URL to the mcps list when defining your CrewAI agent. You can also use MCPServerHTTP with a filter to give your researcher agent searchdocs while restricting other tools.

Q: Can a CrewAI agent update the Glean index automatically?

Yes, you can assign an agent the indexdocument tool. This allows the CrewAI agent to process incoming files and index them into Glean using native gateway authentication during its workflow.

Q: How do CrewAI agents share search context from Glean?

CrewAI agents use shared memory to pass results from searchdatasource between each other. Once one agent retrieves the account logic, the other agents can immediately use that context for their tasks.

Deploy specialized AI agent crews to search, verify, and index enterprise data using CrewAI and Glean.

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Connect Glean MCP to CrewAI

Create your Vinkius account to connect Glean 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 Glean with CrewAI

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Coordinate multi-agent search teams using CrewAI

The `search_docs` tool allows your specialized researcher agents to locate internal documentation inside the Headless Glean Platform. In a CrewAI setup, your researcher agent can find the files, while an analyst agent uses that context to draft a summary for your team. By passing the Glean MCP Server URL directly into your crew's tools list, you give every agent access to your entire SaaS knowledge base. They share memory and context, ensuring they don't repeat searches or miss critical documentation.

Resolve complex corporate queries autonomously

The `get_answer` tool retrieves structured billing rules and answers directly from Glean to resolve complex organizational questions. A CrewAI moderator agent can trigger this tool to fetch verified facts, then pass them to a customer-facing agent to draft an email response. This sequential execution pattern eliminates the need for human intervention. The agents collaborate, verify the sources against your Glean index, and format the output according to your team's specific guidelines.

Clean up outdated indexes with specialized agents

The `delete_document` tool removes obsolete files from your Glean index to keep search results clean and accurate. In CrewAI, you can assign a dedicated janitor agent to run this tool whenever your monitoring agents flag outdated documentation. This automated maintenance loop keeps your search index fresh without manual oversight. The agent inspects internal arrays, identifies the dead links, and calls the tool to wipe them out.

Setup guide

Set up Glean 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 Glean tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You pass the MCP Server URL to the `mcps` list when defining your CrewAI agent. You can also use `MCPServerHTTP` with a filter to give your researcher agent `search_docs` while restricting other tools.

Yes, you can assign an agent the `index_document` tool. This allows the CrewAI agent to process incoming files and index them into Glean using native gateway authentication during its workflow.

CrewAI agents use shared memory to pass results from `search_datasource` between each other. Once one agent retrieves the account logic, the other agents can immediately use that context for their tasks.

Yes, CrewAI supports SSE, stdio, and HTTP transports. You configure the connection method in your Python script to point directly to your managed Glean endpoint on Vinkius.

Yes, your SaaS files and search queries are protected. The MCP connection uses a single-token auth model, routing all traffic through a secure V8 sandbox that never stores your corporate data.

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