How to Use the Google Firestore Collection MCP in CrewAI

Q: How do I connect the Google Firestore Collection MCP Server to a CrewAI agent?

Add the server URL directly to the agent's mcps list during initialization. If you need selective tool exposure, use MCPServerHTTP with a toolfilter.

Q: How do I restrict a CrewAI agent from using the deletedocument tool on this MCP Server?

Use MCPServerHTTP from the crewai.mcp package. This lets you apply a toolfilter so only your supervisor agent can invoke the deletion tool.

Give your CrewAI agent teams a shared memory layer using this Google Firestore Collection MCP Server.

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Connect Google Firestore Collection MCP to CrewAI

Create your Vinkius account to connect Google Firestore Collection 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 Google Firestore Collection with CrewAI

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Shared state management across CrewAI agents

The `set_document` tool lets different agents in your CrewAI team write to the same Firestore document. A researcher agent can write findings, and an analyst agent can update those fields later in the execution chain. You configure this MCP by adding the server URL to the `mcps` list when initializing your CrewAI agents. This gives your entire crew a single source of truth to coordinate their work.

Retrieve Firestore context for specialized CrewAI tasks

The `get_document` tool pulls specific records from Firestore so your specialized CrewAI agents have the exact context they need. For example, a moderator agent can read user history before deciding to trigger an escalation. You can use `MCPServerHTTP` from the `crewai.mcp` package to filter tools, ensuring only authorized CrewAI agents can access this data. This keeps your operational pipelines secure.

Automated CrewAI cleanup of session records

The `delete_document` tool allows your CrewAI supervisor agent to clear temporary session data once a crew execution finishes. This prevents your Firestore collection from getting cluttered with dead operational state. This tool runs autonomously as part of your sequential or hierarchical CrewAI flows. Your agents clean up after themselves without you writing custom cron jobs.

Setup guide

Set up Google Firestore Collection 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 Google Firestore Collection tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Google Firestore Collection 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 Google Firestore Collection. 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 Google Firestore Collection MCP in CrewAI

Add the server URL directly to the agent's `mcps` list during initialization. If you need selective tool exposure, use `MCPServerHTTP` with a `tool_filter`.

Yes, agents share access to the tool. They can write to the same document sequentially or hierarchically as they collaborate on a task.

Use `MCPServerHTTP` from the `crewai.mcp` package. This lets you apply a `tool_filter` so only your supervisor agent can invoke the deletion tool.

The framework supports stdio, SSE, and Streamable HTTP transports. This gives you flexibility depending on whether you run your crew locally or in a cloud environment.

Only your local or hosted CrewAI agents inspect the NoSQL document data. Vinkius handles the connection to this MCP Server via a zero-trust, ephemeral sandbox that never stores your database credentials or document content.

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