Compatible with every major AI agent and IDE
What is the Conductor (Netflix OSS) MCP Server?
Connect your Netflix Conductor instance to any AI agent to orchestrate complex microservices and workflows through natural conversation.
What you can do
- Workflow Management — List all registered workflow definitions, fetch specific versions, and manage the lifecycle of your orchestration logic.
- Task Definitions — Query and manage the underlying task types that power your microservices, ensuring your workers are correctly configured.
- Validation & Testing — Validate workflow JSON definitions before saving them to the server to prevent runtime errors.
- Execution Control — Start new workflow instances asynchronously directly from your AI assistant.
- Batch Operations — Update or create multiple workflow and task definitions in a single request for rapid deployment.
How it works
- Subscribe to this server
- Enter your Conductor Server URL (e.g.,
http://conductor-server:8080) - Start managing your distributed systems from Claude, Cursor, or any MCP-compatible client
Who is this for?
- DevOps Engineers — quickly inspect and update workflow definitions without navigating the Conductor UI
- Backend Developers — validate task configurations and trigger test workflows directly from the IDE
- System Architects — visualize and query the structure of complex distributed processes via natural language
Built-in capabilities (49)
Add a log entry to a task
Bulk pause workflows
Bulk remove workflows
Bulk restart workflows
Bulk resume workflows
Bulk retry workflows
Bulk search workflows by ID
Bulk terminate workflows
Create a new event handler
Create new task definitions
Create a new workflow definition
Delete an event handler
Delete a task definition
Delete a workflow definition
Execute a workflow (Synchronous)
Get pending counts for all queues
Get workflows by correlation ID
Get all event handlers
Get queue depth for a task type
Get running workflow IDs by type
Get a task definition by name
Get all task definitions
Retrieve logs for a task
Get workflow execution by ID
Get a workflow definition by name
Get all workflow definitions
Get all workflow names and versions
Get tasks for a workflow execution
Pause a workflow
Long poll for multiple tasks
Poll for a single task
Remove a workflow from the system
Requeue pending tasks
Rerun a workflow from a specific task
Restart a workflow from the beginning
Resume a paused workflow
Retry the last failed task
Search workflows (returns WorkflowSummary)
Search workflows (returns full Workflow objects)
Skip a task in a running workflow
Start a new workflow execution (Asynchronous)
Terminate a running workflow
Update an existing event handler
Update task result
Update task by reference name
Update a task definition
Update task and poll for the next available task
Create or update workflow definitions (batch)
Validate a workflow definition without saving
Why CrewAI?
When paired with CrewAI, Conductor (Netflix OSS) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Conductor (Netflix OSS) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
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
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
- —
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Conductor (Netflix OSS) in CrewAI
Conductor (Netflix OSS) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Conductor (Netflix OSS) 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 | 4,000+ 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 Conductor (Netflix OSS) in CrewAI
The Conductor (Netflix OSS) 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 49 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
Conductor (Netflix OSS) for CrewAI
Every tool call from CrewAI to the Conductor (Netflix OSS) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I check if my workflow JSON is valid without saving it to the server?
Yes! Use the validate_workflow_definition tool. It allows you to submit a workflow definition JSON for validation, and the server will return any structural or logic errors without persisting the changes.
How do I see all available workflows and their versions?
You can use the get_workflow_names_and_versions tool to get a high-level list of all registered workflows and their associated version numbers.
Is it possible to inspect the configuration of a specific task type?
Yes, use the get_task_definition tool with the specific taskType name. This will return the complete task metadata, including retry logic, timeouts, and input/output keys.
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.
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