Bring Smart Contracts
to CrewAI
Learn how to connect Tenderly (Ethereum Dev Platform) to CrewAI and start using 4 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 Tenderly (Ethereum Dev Platform) MCP Server?
Connect your Tenderly account to any AI agent to streamline your Ethereum development workflow. This MCP server allows you to debug, simulate, and monitor smart contracts through natural language.
What you can do
- Transaction Simulation — Simulate single transactions or complex bundles on any supported network without committing real assets or spending gas.
- Virtual TestNets — Create and manage private mainnet replicas (Virtual TestNets) to test your dApps in a production-like environment with custom configurations.
- On-Chain Monitoring — Set up sophisticated alerts for method calls, state changes, or value transfers to stay informed about blockchain activity in real-time.
- Bundle Execution — Test sequences of transactions to see how they interact, perfect for debugging complex DeFi protocols or multi-step workflows.
How it works
- Subscribe to this server
- Provide your Tenderly Access Key, Account Slug, and Project Slug
- Start simulating transactions and managing testnets from Claude, Cursor, or any MCP client
Who is this for?
- Smart Contract Engineers — debug transactions and verify contract behavior before deployment.
- DeFi Researchers — simulate complex multi-step transactions to analyze protocol interactions.
- Web3 DevOps — monitor production contracts and manage private testing environments seamlessly.
Built-in capabilities (4)
Expression types include method_call, state_change, tx_value, emitted_log, eth_balance. Create an alert on Tenderly
Create a Virtual TestNet on Tenderly
Simulate a bundle of transactions on Tenderly
Simulate a transaction on Tenderly
Why CrewAI?
When paired with CrewAI, Tenderly (Ethereum Dev Platform) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Tenderly (Ethereum Dev Platform) 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
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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
- —
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Tenderly (Ethereum Dev Platform) in CrewAI
Tenderly (Ethereum Dev Platform) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Tenderly (Ethereum Dev Platform) 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 Tenderly (Ethereum Dev Platform) in CrewAI
The Tenderly (Ethereum Dev Platform) 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 4 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
Tenderly (Ethereum Dev Platform) for CrewAI
Every tool call from CrewAI to the Tenderly (Ethereum Dev Platform) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I simulate a transaction without spending real ETH or gas?
Yes! Use the simulate_transaction tool. It runs the transaction against the latest state of the network in a virtual environment, providing full trace and results without any on-chain cost.
How do I create a private fork of Ethereum for testing?
You can use the create_virtual_testnet tool. Provide a slug, display name, and the network ID you want to fork from (e.g., 1 for Mainnet) to spin up a private RPC endpoint.
Can I monitor specific smart contract events automatically?
Absolutely. Use the create_alert tool with an alert_config object to monitor method calls, state changes, or emitted logs on any contract address.
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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