How to Use the Lokalise MCP in Pydantic AI

Q: Can Pydantic AI manage Lokalise project setup tasks?

Yes, the agent can use createproject and getproject to manage translation workspaces. Every project configuration returned by the API is parsed into a type-safe model before your agent can act on it.

Q: How do I handle rate limits when updating keys?

You can use updatekey and listkeys within a validated loop. If the API returns a rate limit error, Pydantic AI's structured error handling lets you catch the exception and back off safely.

Run type-safe localization pipelines with Pydantic AI and the Lokalise MCP Server for guaranteed schema validation.

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Connect Lokalise MCP to Pydantic AI

Create your Vinkius account to connect Lokalise to Pydantic AI 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 Lokalise with Pydantic AI

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Runtime-Validated Key Creation

The `create_key` tool registers new translation keys with strict schema guarantees. Pydantic AI validates the key properties at runtime, ensuring your agent never sends malformed payloads to the API. If the agent attempts to write an invalid key structure, the framework raises a validation error immediately. This prevents corrupted data from entering your localization database.

Validate your MCP Server translation outputs

The `list_translations` tool pulls active strings for validation against your localized data models. Pydantic AI parses the raw API response directly into structured Python models. The agent uses `list_languages` to verify locale codes before executing updates. If a language code does not match your strict Pydantic schema, the execution halts before any files are modified.

Automated File Transfers

The `upload_file` tool pushes localization files up to your target project. The agent reads local JSON or YAML files, validates their structure using Pydantic, and then executes the upload. To pull translations back, the agent calls `download_file` to generate a bundle. It unpacks the bundle and validates every localized string against your application's expected types.

Setup guide

Set up Lokalise MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "lokalise-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Lokalise tools.",
)

result = await agent.run("List recent Lokalise transactions")
print(result.output)

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Common questions about Lokalise MCP in Pydantic AI

Use the MCPToolset class pointing to the Vinkius HTTP endpoint. Pass the toolset instance directly into your Agent constructor to give your model access to the translation tools.

The framework will fail loudly with a validation error instead of passing bad data to your agent. This ensures your code never processes incomplete translation keys or missing locale fields.

Yes, the agent can use create_project and get_project to manage translation workspaces. Every project configuration returned by the API is parsed into a type-safe model before your agent can act on it.

You can use update_key and list_keys within a validated loop. If the API returns a rate limit error, Pydantic AI's structured error handling lets you catch the exception and back off safely.

Your API token and localization payloads are sent securely to the Vinkius gateway. This MCP Server runs in a secure, ephemeral V8 isolate that handles authentication on your behalf, keeping your keys private.

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