How to Use the Crowdin MCP in CrewAI
Deploy a team of AI agents with CrewAI to fully automate your Crowdin localization operations, from monitoring to reporting.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Crowdin MCP to CrewAI
Create your Vinkius account to connect Crowdin 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.
Autonomous Project Monitoring Crew
With CrewAI, you don't just run a script; you deploy a team. Create a "Scout" agent that uses `list_projects` and `list_project_files` to find files with low translation progress. It's always watching your projects. When the Scout finds a stalled file, it passes the job to an "Analyst" agent. The Analyst uses `get_file_details` and `list_project_tasks` to figure out who is assigned and why it's delayed. It’s a specialized crew managing your localization pipeline for you.
A CrewAI Team for Financial Ops
Automate your financial reporting. A "Watcher" agent can be tasked to only use `list_project_reports` and look for new "Translation Costs" reports. It does nothing else. Once it finds a new report, it hands it off to a "Summarizer" agent. This second agent's job is to parse the report data and post a clean summary to a finance channel. This whole process runs 24/7, powered by your CrewAI team and this MCP Server.
Automated Project Onboarding
Spin up a crew to handle new project setups. An "Intake" agent can monitor for new projects and use `list_supported_languages` to check that the language codes are valid. It then passes the project to a "Provisioner" agent. This agent's role is to use `list_glossaries` and `list_translation_memories` to make sure the standard company resources are attached. The crew ensures every project is configured correctly from day one.
Set up Crowdin MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. 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
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke Crowdin tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Crowdin Analyst",
goal="Access and analyze Crowdin data via MCP.",
backstory="Expert analyst with direct Crowdin access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Crowdin transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
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="Crowdin Analyst",
goal="Access and analyze Crowdin data via MCP.",
backstory="Expert analyst with direct Crowdin access.",
tools=mcp_tools,
)
task = Task(
description="List recent Crowdin transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Crowdin. 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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Real-time monitoring
Live
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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
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place for every integration
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Common questions about Crowdin MCP in CrewAI
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