Bring Web3 Authentication
to CrewAI
Learn how to connect Dynamic (Web3 Auth) to CrewAI and start using 8 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Dynamic (Web3 Auth) MCP Server?
Connect your Dynamic environment to any AI agent to streamline Web3 user management and security workflows through natural conversation.
What you can do
- User Management — Fetch detailed user profiles or permanently delete users from specific environments using
get_useranddelete_user. - Security & Compliance — Use
check_sanctionsto verify if specific wallet addresses are sanctioned across multiple chains (ETH, SOL, EVM, etc.). - Session Control — Instantly terminate active user sessions with
revoke_sessionto maintain environment security. - Infrastructure Monitoring — List active embedded wallet versions and configured webhooks to audit your auth setup.
- Financial Insights — Retrieve real-time token balances for users across different networks using
get_token_balances.
How it works
- Subscribe to this server
- Enter your Dynamic API Token
- Start managing your Web3 auth layer from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Web3 Developers — Debug user profiles and check token balances directly from your code editor.
- Security & Ops Teams — Audit wallet sanctions and revoke suspicious sessions instantly without opening the dashboard.
- Product Managers — Monitor webhook configurations and available event types to coordinate feature releases.
Built-in capabilities (8)
Check wallet sanctions
Delete a user from an environment
Get active embedded wallet versions
Get available event types
Get token balances for a user
Get a user by ID in an environment
Get configured webhooks
Revoke an active user session
Why CrewAI?
When paired with CrewAI, Dynamic (Web3 Auth) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Dynamic (Web3 Auth) 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
Dynamic (Web3 Auth) in CrewAI
Dynamic (Web3 Auth) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Dynamic (Web3 Auth) 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 Dynamic (Web3 Auth) in CrewAI
The Dynamic (Web3 Auth) 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 8 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
Dynamic (Web3 Auth) for CrewAI
Every tool call from CrewAI to the Dynamic (Web3 Auth) 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 a specific wallet address is sanctioned before onboarding a user?
Yes! Use the check_sanctions tool by providing the wallet address and the chain (e.g., ETH, SOL). The agent will return the sanction status for that environment.
How do I retrieve the token balances for a user across different networks?
Simply use the get_token_balances tool. You'll need to provide the environment ID, user ID, and an array of balance requests specifying the address and chain.
Is it possible to terminate a suspicious user session immediately?
Yes. Use the revoke_session tool with the specific session ID. This will instantly invalidate the session and disconnect the user.
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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