Weblate MCP Server for CrewAIGive CrewAI instant access to 32 tools to Add Group Admins, Add Group Roles, Create Group, and more
GDPR Free for SubscribersConnect your CrewAI agents to Weblate through Vinkius, pass the Edge URL in the `mcps` parameter and every Weblate tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
Ask AI about this MCP Server for CrewAI
The Weblate MCP Server for CrewAI is a standout in the Developer Tools category — giving your AI agent 32 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminifrom crewai import Agent, Task, Crew
agent = Agent(
role="Weblate Specialist",
goal="Help users interact with Weblate effectively",
backstory=(
"You are an expert at leveraging Weblate 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 Weblate "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 32 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* 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 Weblate MCP Server
Connect your Weblate instance to any AI agent to streamline your continuous localization and translation management through natural conversation.
When paired with CrewAI, Weblate becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Weblate 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 & Component Management — List all projects, fetch component details, and explore translation files directly from the Weblate API.
- Language Insights — Retrieve detailed statistics for specific languages to track translation progress and identify missing strings.
- User & Group Administration — Manage user profiles, list contributions, and handle group roles or administrative permissions.
- Repository Operations — Perform critical repository actions like pulling updates or pushing translations to keep your version control in sync.
- Notification Control — List and manage user notification subscriptions to stay updated on translation changes.
The Weblate MCP Server exposes 32 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 32 Weblate tools available for CrewAI
When CrewAI connects to Weblate through Vinkius, your AI agent gets direct access to every tool listed below — spanning translation-management, localization-workflow, i18n, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Add group admins on Weblate
Add team administrators to a group
Add group roles on Weblate
Associate roles with a group
Create group on Weblate
Create a new group
Create language on Weblate
Create a new language definition
Create project on Weblate
Create a new project
Create project component on Weblate
Create a new component in a project
Create role on Weblate
Create a new role with specific permissions
Create user on Weblate
Create a new Weblate user
Delete user on Weblate
Delete a user (marks inactive)
Get group on Weblate
Get group details (roles, projects, components)
Get language on Weblate
Get language details (plural formulas, aliases)
Get language statistics on Weblate
Global statistics for a language
Get project on Weblate
Get project details
Get project file url on Weblate
Get the URL to download all translations as a ZIP archive
Get project repository on Weblate
Overall VCS status for the project
Get role on Weblate
Get role details and permission codenames
Get root on Weblate
Get Weblate API root entry point
Get user on Weblate
Get detailed user information
Get user contributions on Weblate
List translations with user contributions
Get user statistics on Weblate
Get user translation statistics
List groups on Weblate
List Weblate groups
List languages on Weblate
List all languages
List project components on Weblate
List components within a project
List project labels on Weblate
Manage project labels
List project languages on Weblate
Paginated statistics for all languages in a project
List projects on Weblate
List all projects
List roles on Weblate
List roles associated with the user
List user notifications on Weblate
List user notification subscriptions
List users on Weblate
Requires management permissions or returns self. List Weblate users
Manage user notifications on Weblate
Manage user notification subscriptions
Perform repository operation on Weblate
Perform VCS operations (push, pull, commit, reset, cleanup)
Update user on Weblate
Update user details
Connect Weblate to CrewAI via MCP
Follow these steps to wire Weblate into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install CrewAI
pip install crewaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.comCustomize the agent
role, goal, and backstory to fit your use caseRun the crew
python crew.py. CrewAI auto-discovers 32 tools from WeblateWhy Use CrewAI with the Weblate MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Weblate 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
Weblate + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Weblate MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Weblate 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 Weblate, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Weblate 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 Weblate against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Example Prompts for Weblate in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Weblate immediately.
"List all active localization projects in Weblate."
"Show me the translation statistics for the German language."
"Get detailed information for user 'johndoe'."
Troubleshooting Weblate MCP Server with CrewAI
Common issues when connecting Weblate to CrewAI through Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Weblate + CrewAI FAQ
Common questions about integrating Weblate MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
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?
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?
Can CrewAI agents call multiple MCP tools in parallel?
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)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Explore More MCP Servers
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