What kind of Lokalise API token do I need for this integration?

You need a Personal Access Token from your Lokalise account. Go to your profile settings, find the API Tokens section, and generate a new token with read/write access to projects. Keep this token secure as it grants full API access to your account.

How do I add a new translation key to my Lokalise project via the AI agent?

Use the `create_key` action with the project ID, key name (e.g., `homepage.welcome.title`), and optionally specify platforms, tags, and a description. The key will be created with the base language placeholder ready for translation.

Can I export all my translations in a specific format like JSON or YAML?

Yes! Use the `download_file` action and specify the `format` parameter (e.g., `json`, `yml`, `xliff`, `strings`, `xml`). You can also filter by specific languages or filenames to generate targeted export bundles.

Is it possible to add translations programmatically for multiple languages at once?

Yes. The `add_translation` action supports adding translations for one or more keys at once. You can also mark translations as fuzzy or reviewed to indicate their quality status in the workflow.

Lokalise MCP Server for CrewAI 13 tools — connect in under 2 minutes

Name: Lokalise
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 13 Tools Framework

Connect your CrewAI agents to Lokalise through Vinkius, pass the Edge URL in the `mcps` parameter and every Lokalise tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Lokalise Specialist",
    goal="Help users interact with Lokalise effectively",
    backstory=(
        "You are an expert at leveraging Lokalise tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Lokalise "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 13 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Lokalise MCP Server

Connect your Lokalise account to any AI agent and take full control of your translation and localization workflows through natural conversation.

When paired with CrewAI, Lokalise becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Lokalise tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Project Management — List all translation projects, fetch detailed project metadata, and create new projects directly from the API
Key Management — Query translation keys with filters by platform, tags, or filenames, plus create and update keys programmatically
Translation Operations — Fetch translations for any key, add new translations with review/fuzzy flags, and manage multi-language content
File Import/Export — Upload localization files (JSON, YAML, XLIFF) and generate download bundles in any supported format
Team & Orders — List team members and their roles, plus inspect professional translation orders

The Lokalise MCP Server exposes 13 tools through the Vinkius. Connect it to CrewAI 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 Lokalise to CrewAI via MCP

Follow these steps to integrate the Lokalise MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 13 tools from Lokalise

Why Use CrewAI with the Lokalise MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Lokalise through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Lokalise + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Lokalise MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Lokalise for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Lokalise, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Lokalise tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Lokalise against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Lokalise MCP Tools for CrewAI (13)

These 13 tools become available when you connect Lokalise to CrewAI via MCP:

add_translation

Add translations to one or more keys

create_key

Create translation keys in a Lokalise project

create_project

Create a new Lokalise project

download_file

Generate a download bundle of translations

get_project

Get details of a specific Lokalise project

list_keys

List translation keys in a Lokalise project

list_languages

List languages in a Lokalise project

list_orders

List translation orders in your Lokalise account

list_projects

List all Lokalise projects

list_team_members

List all team members in your Lokalise account

list_translations

List translations for a key in a Lokalise project

update_key

Update an existing translation key

upload_file

Upload a localization file to a Lokalise project

Example Prompts for Lokalise in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Lokalise immediately.

"List all my Lokalise translation projects and show their current status."

"Create a new translation key 'checkout.success.message' in my Web App project for the web platform."

"Download all Portuguese (pt-BR) translations from my Mobile App project in JSON format."

Troubleshooting Lokalise MCP Server with CrewAI

Common issues when connecting Lokalise to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Lokalise + CrewAI FAQ

Common questions about integrating Lokalise MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.