How to Use the Mattermost MCP in Google ADK

Q: Can I restrict which Mattermost tools Google ADK sees?

You can pass a toolnames filter to the McpToolset. This limits the agent to only the functions you choose to expose.

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Connect Mattermost MCP to Google ADK

Create your Vinkius account to connect Mattermost to Google ADK 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 Mattermost with Google ADK

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Connect Mattermost to Google ADK agents

Your agent uses `list_teams` and `list_team_channels` to map out your organization. It pulls this data into the Google ADK environment to ground its reasoning in your actual team structure. This setup allows the agent to navigate your workspace. It sees exactly what you see, making it a functional member of your team.

Process chat history with Google ADK

The agent reads past discussions using `list_channel_posts` to understand context before taking action. It processes these threads alongside your BigQuery data to provide better answers. By calling `post_message` after a reasoning step, the agent closes the loop on tasks. It works as an extension of your existing Google Cloud infrastructure.

Verify Mattermost configuration in Google ADK

Run `get_server_config` to ensure your agent is hitting the right instance. The agent validates settings on the fly, preventing configuration drift in your production environment. Use `test_server_ping` to confirm the link is active. If the connection drops, your agent knows immediately and avoids failing silently.

Setup guide

Set up Mattermost MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Mattermost tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Mattermost_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Mattermost tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Mattermost MCP in Google ADK

Yes, you use the McpToolset class to integrate the server. It maps the tools into your agent's namespace for immediate use.

The framework treats tool responses as structured input. You can pass these results directly into your LLM prompt for long-context reasoning.

You can pass a tool_names filter to the McpToolset. This limits the agent to only the functions you choose to expose.

It supports standard HTTP transport. As long as your agent can reach the server endpoint, the integration works as expected.

This server acts as a gateway for raw text and metadata. It does not store your message history, ensuring your sensitive communications remain on your server.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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