Bring Gantt Charts
to CrewAI
Learn how to connect TeamGantt to CrewAI and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the TeamGantt MCP Server?
Connect your TeamGantt account to any AI agent and simplify how you manage your project timelines, task assignments, and team resources through natural conversation.
What you can do
- Project Oversight — List all projects in your account and retrieve detailed metadata and configuration for specific Gantt charts.
- Task Management — Create, update, and delete tasks with full control over start/end dates and completion percentages.
- Timeline Coordination — Create dependencies between tasks to ensure your project logic remains sound and automated.
- Resource Tracking — List available resources (people and equipment) to optimize team allocation across projects.
- Milestone Planning — List and query major project goals (milestones) and sub-task checklists.
- Account Visibility — Fetch your user profile and verify account configurations directly from the agent.
How it works
1. Subscribe to this server
2. Enter your TeamGantt API Token (found in your account settings under API)
3. Start managing your timelines from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Project Managers — quickly check task progress and update project timelines via simple AI commands.
- Operations Teams — coordinate resource assignments and verify dependencies directly from the workspace.
- Engineering Leads — monitor milestones and update task completion percentages via the AI assistant.
Built-in capabilities (12)
Add task to project
Get user info
Get project info
List sub-tasks
Get task details
g. Task A must finish before Task B starts). Create Gantt link
List users and labels
List major goals
List tasks in project
List TeamGantt projects
Delete task
). Update task status/dates
Why CrewAI?
When paired with CrewAI, TeamGantt becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call TeamGantt tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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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
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter 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
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Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
TeamGantt in CrewAI
TeamGantt and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect TeamGantt to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for TeamGantt in CrewAI
The TeamGantt 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. All 12 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
TeamGantt for CrewAI
Every tool call from CrewAI to the TeamGantt MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I see all the tasks in a project via AI?
Yes! Use the list_project_tasks tool and provide the Project ID. Your agent will retrieve all tasks, milestones, and groups for that specific Gantt chart.
How do I update the progress of a task using the agent?
Use the update_task_fields action. Provide the Task ID and the percentComplete value (0-100) to update the task's status instantly.
Is it possible to link two tasks with a dependency via AI?
Absolutely. Use the link_tasks_dependency tool. Provide the ID of the predecessor and the successor tasks to create a Gantt link between them.
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.
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.