Bring Marketing Analytics
to CrewAI
Learn how to connect Reportei to CrewAI and start using 10 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Reportei MCP Server?
Connect your Reportei account to any AI agent and take full control of your digital marketing orchestration and reporting workflows through natural conversation. Reportei provides a premier platform for consolidating metrics from social networks and ad platforms, and this integration allows you to retrieve project metadata, monitor report generation, and log important timeline events directly from your chat interface.
What you can do
- Project & Client Orchestration — List all managed marketing projects and retrieve detailed client metadata programmatically.
- Report & Analysis Intelligence — Access and monitor generated reports and retrieve detailed performance metadata directly from the AI interface.
- Metric & Performance Tracking — Retrieve real-time data from connected channels like Instagram, Facebook, and Google Ads via natural language.
- Timeline & Event Control — Create and list project timeline events to maintain a comprehensive history of marketing actions and results.
- Operational Monitoring — Track system activity and manage project settings using simple AI commands to ensure your reporting is always optimized.
How it works
1. Subscribe to this server
2. Enter your Reportei API Token from your account settings
3. Start managing your marketing reports from Claude, Cursor, or any MCP-compatible client
No more manual data collection or complex spreadsheet reporting. Your AI acts as a dedicated marketing analyst or account coordinator.
Who is this for?
- Marketing Agencies — quickly retrieve client results and monitor project timelines without switching apps.
- Social Media Managers — automate the extraction of performance metrics and track campaign milestones via natural conversation.
- Data Analysts — streamline the retrieval of consolidated marketing data directly within the chat.
Built-in capabilities (10)
Add a timeline event
Generate a new analytics report
Get details for a specific client
Get details for a specific report
Get raw metrics data
List all clients
List all connected integrations
List all marketing projects
You can filter by project ID. List generated reports
List timeline events
Why CrewAI?
When paired with CrewAI, Reportei becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Reportei 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
Reportei in CrewAI
Reportei and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Reportei 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 Reportei in CrewAI
The Reportei 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 10 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
Reportei for CrewAI
Every tool call from CrewAI to the Reportei MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can my AI automatically find the details for a specific project just by providing its ID?
Yes! Use the list_reportei_projects tool. Your agent will respond with complete metadata for all your projects, allowing you to identify and inspect individual client accounts in seconds.
How do I find my Reportei API Token?
Log in to your Reportei account, navigate to Settings > Company > Reportei API, and you will find your unique secret token there.
Can I retrieve metrics for a specific date range?
Yes, using the get_reportei_metrics tool, you can provide start_date and end_line parameters to fetch consolidated marketing data for any specific period.
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.