Crowdin MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Crowdin through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Crowdin "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Crowdin?"
)
print(result.data)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Crowdin MCP Server
Integrate Crowdin, the leading localization management platform, directly into your AI workflow. Manage your translation projects, monitor file statuses, and track localization tasks using natural language.
Pydantic AI validates every Crowdin tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- Project Management — List and retrieve detailed settings and statuses for all your localization projects.
- File Operations — Monitor files within projects and retrieve specific file metadata.
- Task & Workflow Tracking — Track translation and proofreading tasks to ensure timely delivery.
- Resource Insights — Access glossaries, translation memories, and supported language lists via chat.
The Crowdin MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Crowdin to Pydantic AI via MCP
Follow these steps to integrate the Crowdin MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Crowdin with type-safe schemas
Why Use Pydantic AI with the Crowdin MCP Server
Pydantic AI provides unique advantages when paired with Crowdin through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Crowdin integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Crowdin connection logic from agent behavior for testable, maintainable code
Crowdin + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Crowdin MCP Server delivers measurable value.
Type-safe data pipelines: query Crowdin with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Crowdin tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Crowdin and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Crowdin responses and write comprehensive agent tests
Crowdin MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Crowdin to Pydantic AI via MCP:
get_file_details
Touches file structure, revision history, and per-language translation status boundaries. Get metadata for a specific file in a project
get_project_details
Touches source/target language settings and project-level activity summary boundaries. Get detailed settings and status for a project
list_glossaries
Resolves glossary names, IDs, and language pairs used for terminology management. List all glossaries available in the account
list_project_files
Resolves file names, IDs, paths, and current translation progress metrics. List all files within a specific project
list_project_reports
Resolves report names, types (Translation Costs, Progress), and creation timestamps. List generated reports for a specific project
list_project_screenshots
Resolves screenshot IDs, tags, and linked string identifiers used for visual context. List all screenshots uploaded to a project for context
list_project_tasks
Resolves task titles, types (Translation, Proofreading), status, and assigned linguist references. List translation and proofreading tasks for a project
list_projects
Resolves project names, IDs, source languages, and target languages for localization workflows. List all localization projects in your Crowdin account
list_supported_languages
Resolves language codes, human-readable names, and locale identifiers. List all languages supported by Crowdin
list_translation_memories
Resolves TM names, IDs, and segment counts for reuse in future translations. List all translation memories (TMs) available
Example Prompts for Crowdin in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Crowdin immediately.
"List all localization projects in my account."
"What is the status of files in project 'Mobile App'?"
"List all active translation tasks for my projects."
Troubleshooting Crowdin MCP Server with Pydantic AI
Common issues when connecting Crowdin to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiCrowdin + Pydantic AI FAQ
Common questions about integrating Crowdin MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Crowdin with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Crowdin to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.