Compatible with every major AI agent and IDE
What is the Unleash (Feature Toggles) MCP Server?
Connect your Unleash instance to any AI agent and gain full control over your feature management lifecycle through natural conversation.
What you can do
- Feature Evaluation — Fetch all feature flags and strategies for server-side evaluation or evaluate specific flags for client-side contexts using User IDs and properties.
- Project & Environment Audit — List all Unleash projects, environments, and segments to understand your infrastructure layout.
- Flag Management — Inspect all feature flags within specific projects to verify rollout statuses and strategy configurations.
- Metrics & Registration — Report SDK usage metrics and register new client or frontend instances directly through the agent.
- User Management — Retrieve lists of users and segments to verify targeting rules and access.
How it works
- Subscribe to this server
- Enter your Unleash API URL and API Token (Admin, Client, or Frontend depending on your needs)
- Start managing your feature rollouts from Claude, Cursor, or any MCP-compatible client
Who is this for?
- DevOps & SREs — quickly audit environments and segments without navigating the Unleash UI
- Product Managers — check the status of feature toggles and rollout strategies across different projects
- Software Engineers — verify flag evaluations and context properties directly from the code editor
Built-in capabilities (11)
Fetch all feature flags and strategies for server-side evaluation
Optionally provide context like userId or properties. Fetch enabled feature flags for a specific Unleash Context
Fetches all environments configured in Unleash. List all Unleash environments
Fetches features for a given project ID. List all feature flags in a specific project
Fetches all projects configured in Unleash. List all Unleash projects
Fetches all segments configured in Unleash. List all Unleash segments
Fetches all users configured in Unleash. List all Unleash users
Register a new backend SDK instance
Register a new frontend SDK instance
Report flag usage metrics from a backend SDK
Report flag usage metrics from a frontend SDK
Why CrewAI?
When paired with CrewAI, Unleash (Feature Toggles) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Unleash (Feature Toggles) 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
Unleash (Feature Toggles) in CrewAI
Unleash (Feature Toggles) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Unleash (Feature Toggles) 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 Unleash (Feature Toggles) in CrewAI
The Unleash (Feature Toggles) 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 11 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
Unleash (Feature Toggles) for CrewAI
Every tool call from CrewAI to the Unleash (Feature Toggles) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I evaluate feature flags for a specific user ID?
Yes. Use the get_frontend_features tool and provide the userId. The agent will return the enabled flags based on the Unleash context for that specific user.
How do I see all feature flags associated with a specific project?
You can use the list_project_features tool by providing the projectId. This will list all toggles, their types, and current statuses within that project.
Does this server support listing segments and environments?
Yes, the server includes list_segments and list_environments tools, allowing you to audit your Unleash configuration and targeting rules easily.
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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