Bring Marketing Analytics
to Pydantic AI
Learn how to connect Reportei to Pydantic AI 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 Pydantic AI?
Pydantic AI validates every Reportei tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Reportei integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your Reportei connection logic from agent behavior for testable, maintainable code
Reportei in Pydantic AI
Reportei and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Reportei to Pydantic AI 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 Pydantic AI
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 Pydantic AI 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 Pydantic AI
Every tool call from Pydantic AI 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 Pydantic AI discover MCP tools?
Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
Does Pydantic AI validate MCP tool responses?
Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
Can I switch LLM providers without changing MCP code?
Absolutely. Pydantic AI abstracts the model layer. your Reportei MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai