How to Use the Chess.com MCP in CrewAI

Q: How do I set up a Chess.com scouting team in CrewAI?

Define a scout agent with access to getplayerprofile and an analyst agent with access to getplayerstats. CrewAI will manage their collaboration to generate deep opponent reports.

Deploy specialized agent teams to analyze Chess.com opponents and curate training puzzles with CrewAI.

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Connect Chess.com MCP to CrewAI

Create your Vinkius account to connect Chess.com 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 Chess.com with CrewAI

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Coordinate multi-agent opponent scouting reports

This tool scans opponent profiles using `get_player_profile` and retrieves their active matches with `get_player_current_games`. CrewAI lets you assign a scout agent to gather this data while an analyst agent evaluates their recent openings. The agents share memory to build a detailed tactical profile of your opponent.

Curate training packages using a CrewAI team

This MCP Server gathers tactical setups using `get_random_puzzle` and filters them by rating with `get_player_stats`. Your CrewAI team uses a moderator agent to select puzzles that match your current skill gaps. The supervisor agent manages the flow, ensuring you only receive puzzles that target your weak areas.

Monitor competitive leaderboards autonomously

This tool tracks the best players using `get_leaderboards` and identifies top talent via `get_titled_players`. CrewAI runs a monitoring agent to watch these lists and flag rapid rating climbs among grandmasters. A separate research agent then pulls the player's recent matches to identify emerging opening trends.

Setup guide

Set up Chess.com 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 Chess.com tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Chess.com 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 Chess.com. 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 Chess.com MCP in CrewAI

Define a scout agent with access to `get_player_profile` and an analyst agent with access to `get_player_stats`. CrewAI will manage their collaboration to generate deep opponent reports.

Yes, you can task an agent with fetching your matches using `get_player_monthly_games`. A second agent then reviews the PGN data to pinpoint tactical mistakes.

Agents utilize CrewAI's shared memory to pass FEN strings and solutions retrieved from `get_random_puzzle`. This allows one agent to find puzzles while another formats them into training guides.

Yes, you can restrict access by exposing the MCP Server with specific tool filters. This allows you to block certain endpoints like player search while keeping puzzles open.

Your account is safe because this MCP Server only requests public club, player, and puzzle data. Vinkius runs the process in a zero-trust sandbox, ensuring no credentials or personal logs are leaked.

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