How to Use the Chess.com Global Intelligence MCP in Google ADK

Q: What's the setup for Chess.com Global Intelligence with the Google ADK?

After pip install google-adk, you'll instantiate an McpToolset using your Vinkius server URL. Then you just pass that toolset into your LlmAgent's tools list. The agent discovers the available functions automatically.

Q: Is it possible to filter the tools exposed to my Google ADK agent from Chess.com Global Intelligence?

Yes, the McpToolset in the Google ADK accepts a toolnames argument. You can provide a list of strings to expose only specific functions, like getdailychesspuzzle, to a specialized agent.

Connect Gemini to live Chess.com data and analyze it in BigQuery using the Google ADK.

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Connect Chess.com Global Intelligence MCP to Google ADK

Create your Vinkius account to connect Chess.com Global Intelligence 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 Chess.com Global Intelligence with Google ADK

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Feed BigQuery with Chess Data

This is the fastest way to get Chess.com data into your Google Cloud environment. Your agent can use `get_player_game_archives` and `get_player_monthly_games` to pull down thousands of games. It can also grab player metadata with `get_player_profile` and `get_player_stats`. Since you're using the Google ADK, your Gemini agent can directly pipe this data into BigQuery tables. You can build a data pipeline that runs on a schedule, continuously updating your datasets with the latest games and player ratings without manual oversight.

Long-Context Player Analysis with this MCP Server

Find patterns across a player's entire career. Your agent can fetch all available monthly archives for a player with `get_player_game_archives`, then pull the PGNs for each month using `get_player_monthly_games`. It can also cross-reference tournament performance with `get_tournament_metadata`. Gemini's long-context window is the key here. Your agent can hold a player's complete game history in-context to answer complex questions, like "How did this player's opening choices evolve over the last five years?". This MCP server provides the data; the ADK and Gemini provide the horsepower for deep analysis.

Build Enterprise Agents on Google Cloud

Go beyond simple queries. Use the ADK to build an agent that monitors the `get_global_leaderboards` and triggers a Cloud Function when a new player enters the top 10. Or, have it watch `list_active_streamers` and log the data to a Firestore database. This MCP Server becomes just another toolset for your larger Google Cloud application. The `McpToolset` class makes it simple to integrate. You can even filter which tools are exposed to your `LlmAgent` using the `tool_names` parameter, giving you fine-grained control.

Setup guide

Set up Chess.com Global Intelligence 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 Chess.com Global Intelligence 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="Chess.com Global Intelligence_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Chess.com Global Intelligence tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Chess.com Global Intelligence MCP in Google ADK

After `pip install google-adk`, you'll instantiate an `McpToolset` using your Vinkius server URL. Then you just pass that toolset into your `LlmAgent`'s `tools` list. The agent discovers the available functions automatically.

Yes. That's a core strength of the ADK. Your agent can pull fresh data from the Chess.com Global Intelligence MCP server and combine it with your historical data in BigQuery for a single, unified analysis.

The server provides structured data from Chess.com. Your Gemini agent, configured via the Google ADK, can reason over this data to perform multi-step tasks. For example, it can get a list of titled players with `list_titled_players`, then loop through them to get individual stats with `get_player_stats`.

Yes, the `McpToolset` in the Google ADK accepts a `tool_names` argument. You can provide a list of strings to expose only specific functions, like `get_daily_chess_puzzle`, to a specialized agent.

The server processes requests for public Chess.com information—player stats, game histories, and puzzle data. Your Vinkius auth token is used for access control. Each request is executed in a dedicated, single-use sandboxed environment that is destroyed immediately after, ensuring no data from your session persists.

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