Compatible with every major AI agent and IDE
What is the Mitto MCP Server?
Connect your Mitto account to any AI agent to handle global communication workflows through natural conversation.
What you can do
- SMS Messaging — Send single or bulk SMS messages globally with custom sender IDs and delivery tracking.
- Two-Factor Authentication (2FA) — Generate, send, and verify OTP codes via SMS or Voice channels to secure your user accounts.
- Number Lookup — Validate phone numbers and retrieve carrier information to ensure deliverability.
- Usage Analytics — Monitor your SMS and 2FA usage statistics grouped by country or date ranges.
- Application Management — Manage your Mitto applications and masked numbers for privacy-focused communication.
How it works
- Subscribe to this server
- Enter your Mitto API Key
- Start sending messages and verifying users from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Developers — integrate SMS notifications and 2FA into apps without leaving the IDE
- Support Teams — send quick updates or verification codes to customers via chat
- Marketing Teams — manage bulk SMS campaigns and track conversion rates directly
Built-in capabilities (27)
Add a masked number
Add a masking participant
Cancel a 2FA OTP request
Create a number masking application
Create a masking context
Delete a masked number
Delete a number masking application
Delete a masking context
Delete a masking participant
Get 2FA usage records
Get SMS usage by country
List masked numbers
List number masking applications
List masking contexts
List masking participants
Lookup mobile number information
Search 2FA SDRs
Search masking interactions
Send a 2FA OTP message
Send bulk SMS messages
Send a single SMS message
Set 2FA limits
g., SMS to Voice) for 2FA. Set 2FA workflows
Track SMS conversion
Update a number masking application
Update a masking context
Verify a 2FA OTP code
Why Pydantic AI?
Pydantic AI validates every Mitto tool response against typed schemas, catching data inconsistencies at build time. Connect 27 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.
- —
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 Mitto 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 Mitto connection logic from agent behavior for testable, maintainable code
Mitto in Pydantic AI
Mitto and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Mitto 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 | 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 Mitto in Pydantic AI
The Mitto 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 27 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
Mitto for Pydantic AI
Every tool call from Pydantic AI to the Mitto MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I send an SMS to multiple phone numbers at the same time?
Yes! Use the send_bulk_sms tool. You can provide an array of recipient numbers in E.164 format and a single message body to reach multiple users at once.
How do I verify a security code sent to a user?
After sending a code with send_2fa, use the verify_2fa tool. You will need the requestId from the initial send and the code provided by the user to confirm their identity.
Can I check which countries I am sending the most messages to?
Yes, the get_sms_usage_by_country tool allows you to retrieve usage statistics grouped by country, helping you analyze your global communication reach.
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 Mitto MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
MCPServerHTTP not found
Update: pip install --upgrade pydantic-ai
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