How to Use the RAWG Video Games Database MCP in CrewAI

Q: Can multiple CrewAI agents query the RAWG Video Games Database simultaneously?

Yes. Your researcher agent can use searchvideogames while your analyst agent concurrently runs getvideogamedetails to speed up your crew's throughput.

Run cooperative agent teams with CrewAI to research and analyze the RAWG Video Games Database autonomously.

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Connect RAWG Video Games Database MCP to CrewAI

Create your Vinkius account to connect RAWG Video Games Database to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup RAWG Video Games Database with CrewAI

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Assign game research tasks to specialized CrewAI agents

The `search_video_games` tool allows your research agent to track down titles across RAWG's library of half a million entries. Your agent uses this tool to locate exact matches and hand the raw data over to your analyst agents. Because CrewAI relies on role-based specialization, your researcher agent can focus entirely on querying this MCP Server. It gathers raw candidate lists and passes them down the chain for deeper evaluation.

Extract deep video game details for collaborative analysis

The `get_video_game_details` tool pulls complete game profiles, developer records, and ratings. Your analyst agent runs this tool on specific game IDs to evaluate the quality and history of each title. This collaborative setup lets one agent find the games while another analyzes their details. The MCP Server acts as the single source of truth, feeding consistent game data into your crew's shared memory.

Map console compatibility across autonomous crews

The `list_video_game_platforms` tool fetches the full list of active gaming consoles and operating systems. Your compatibility agent uses this tool to verify where a game can actually be played. Instead of guessing hardware compatibility, your crew uses this MCP tool to verify support. This prevents your agents from recommending Xbox exclusives to users who specified they only own a Switch.

Setup guide

Set up RAWG Video Games Database 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 RAWG Video Games Database tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent RAWG Video Games Database 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 RAWG. 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 RAWG Video Games Database MCP in CrewAI

Pass the Vinkius HTTP endpoint directly into your agent's mcps list. The agent will automatically discover MCP tools and use them when researching titles.

Yes. Your researcher agent can use search_video_games while your analyst agent concurrently runs get_video_game_details to speed up your crew's throughput.

Yes. You can use the MCPServerHTTP class with an MCP tool filter to expose only list_video_game_platforms to specific agents while keeping other tools hidden.

It uses secure Streamable HTTP and SSE transports managed by Vinkius. This ensures fast, reliable communication between your python crew and the database.

All credentials are isolated within ephemeral V8 sandboxes. Your search queries and API keys are never written to persistent storage, ensuring complete zero-trust execution.

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