How to Use the Appwrite MCP in Google ADK

Q: Can Google ADK agents filter Appwrite tools?

Yes. Use the toolnames filter in your McpToolset setup to restrict which functions your agent can call. This keeps your backend interactions limited and secure.

Connect your Appwrite backend to the Google ADK to let your Gemini-powered agents act on your databases and storage.

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Connect Appwrite MCP to Google ADK

Create your Vinkius account to connect Appwrite 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 Appwrite with Google ADK

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Navigate Appwrite databases via Google ADK

Trigger `list_databases`, `list_collections`, and `list_documents` to feed your model the exact records it needs. This works perfectly with Gemini's high-token context to analyze large datasets. Your agents query specific collections without needing manual SQL exports. It turns your database into a readable source for long-context reasoning.

Control storage buckets with Google ADK

Use `list_storage_buckets` to discover your assets and `list_bucket_files` to pull content lists. Your agent knows exactly what files are available in your project. This gives your Google Cloud agents direct visibility into your storage. It avoids the friction of manual file management.

Automate function oversight using Google ADK

Query `list_functions` to see what code is deployed and `list_function_executions` to audit recent runs. Your agents get a direct line to your serverless performance metrics. This allows your infrastructure agents to report on execution trends. You get automated insights into how your backend functions perform.

Setup guide

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

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Common questions about Appwrite MCP in Google ADK

Install the google-adk package and define your server parameters using McpToolset. You can then pass this toolset into your LlmAgent to start querying your data.

Yes. Use the tool_names filter in your McpToolset setup to restrict which functions your agent can call. This keeps your backend interactions limited and secure.

Yes, it supports both Stdio and HTTP transports. Pick the one that fits your Google Cloud deployment architecture best.

Gemini models handle 1M+ tokens, so they ingest your collection lists easily. You can pull deep context from your databases without hitting limits.

Your project data is never shared with external trainers. The server acts as a secure pipe, only exposing the specific user records needed for the agent's current task.

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