How to Use the Zulip MCP in Google ADK

Q: How does Zulip and Google ADK manage context?

The agent uses the zulipgetmessages tool to pull relevant history, which it feeds into Gemini models. Since these models support 1M+ tokens of context, they can hold deep, complex knowledge about long-running conversations within Zulip.

Q: Can I use Zulip and Google ADK for internal process automation?

Yes. You'll list users with zulipgetusers first, then build workflows that might trigger a message via zulipsendmessage. This makes the agent perfect for automating repeatable internal processes.

Q: Does Zulip and Google ADK support direct messaging?

The zulipsendmessage tool supports this. When you set the message type to 'direct', your agent sends a private message between two users in Zulip.

Q: What data types can I access with Zulip and Google ADK?

The server lets your agent read user profiles (zulipgetownprofile), stream topics, complete message histories, and the list of all users in the organization.

Run enterprise Zulip automation with Google ADK on BigQuery.

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Connect Zulip MCP to Google ADK

Create your Vinkius account to connect Zulip 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 Zulip with Google ADK

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Reading message history

The `zulip_get_messages` tool retrieves full message histories. By using the 'newest' anchor, your agent gets the absolute latest messages for context. This is key when running long-context reasoning with Gemini models. Your agent pulls this data and feeds it into a model that can hold over 1 million tokens, allowing it to track complex discussions across many pages of Zulip chat.

List organizational units

You can list all available streams with `zulip_get_streams`, or get a user directory using `zulip_get_users`. These tools provide the structural data your agent needs before it executes any action. When building enterprise agents on Google Cloud, having accurate listing capabilities prevents the agent from trying to talk to non-existent channels.

Publish messages via MCP Server

To send a message, use `zulip_send_message`. It handles both 'stream' type posts and direct DMs. This simple function lets your agent keep up with real-time conversation flow. It’s the simplest way to let an autonomous system act on behalf of a user without having to write complex API wrappers for every single message type.

Setup guide

Set up Zulip 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 Zulip 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="Zulip_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Zulip tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Zulip MCP in Google ADK

The agent uses the `zulip_get_messages` tool to pull relevant history, which it feeds into Gemini models. Since these models support 1M+ tokens of context, they can hold deep, complex knowledge about long-running conversations within Zulip.

Yes. You'll list users with `zulip_get_users` first, then build workflows that might trigger a message via `zulip_send_message`. This makes the agent perfect for automating repeatable internal processes.

The `zulip_send_message` tool supports this. When you set the message type to 'direct', your agent sends a private message between two users in Zulip.

The server lets your agent read user profiles (`zulip_get_own_profile`), stream topics, complete message histories, and the list of all users in the organization.

This server touches user profiles and messages. Given its integration with BigQuery, make sure your agents only process message content that is explicitly required for the task.

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