Bring Shared Inbox
to Pydantic AI
Learn how to connect Gmelius to Pydantic AI and start using 9 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Gmelius MCP Server?
Connect your Gmelius account to any AI agent and take full control of your team's collaborative workspace and high-fidelity shared inbox orchestration through natural conversation.
What you can do
- Conversation Portfolio Orchestration — List all collaborative email threads, retrieve detailed high-fidelity history, and monitor ticket status programmatically
- Kanban Pipeline Intelligence — Query team project boards, retrieve detailed technical metadata, and stay on top of workflow progress in real-time
- Card & Task Orchestration — Programmatically generate new task cards or email items on specific boards directly through your agent for perfectly coordinated delivery
- Sequence Monitoring — Access configured automated high-fidelity email sequences and monitor their status directly through your agent for outreach optimization
- Template Discovery — Access your complete directory of high-fidelity shared email templates and inboxes to choose the right context for every interaction
- Operational Monitoring — Verify account-level API connectivity and monitor collaborative volume directly through your agent for perfectly coordinated service scaling
How it works
1. Subscribe to this server
2. Retrieve your Access Token from your Gmelius dashboard (Settings > API)
3. Start managing your collaborative growth from Claude, Cursor, or any MCP client
No more manual status updates or jumping between shared inboxes. Your AI acts as your dedicated collaboration coordinator and shared inbox architect.
Who is this for?
- Team Leads — instantly retrieve project board statuses and monitor team responsiveness using natural language commands without leaving your creative workspace
- Customer Success Managers — verify high-fidelity conversation history and manage shared tags to ensure healthy client relationships
- Operations Managers — analyze collaborative workflows and monitor sequence performance through simple AI queries
Built-in capabilities (9)
Check API Status
Add a new card to a board
Get details for a specific board
Get details for a specific conversation
List cards on a Kanban board
List collaborative Kanban boards
List Gmelius shared conversations
List email sequences
List shared email templates
Why Pydantic AI?
Pydantic AI validates every Gmelius tool response against typed schemas, catching data inconsistencies at build time. Connect 9 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 Gmelius 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 Gmelius connection logic from agent behavior for testable, maintainable code
Gmelius in Pydantic AI
Gmelius and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Gmelius 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 Gmelius in Pydantic AI
The Gmelius 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 9 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
Gmelius for Pydantic AI
Every tool call from Pydantic AI to the Gmelius MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I find my Gmelius Access Token?
Log in to your account, navigate to Account Settings > API, and register a new high-fidelity API App to obtain your Bearer token.
Can I check board card details via AI?
Yes! The list_gmelius_board_cards tool allows your agent to retrieve high-fidelity metadata including description and status for all cards on a board.
How do I list my shared email sequences?
Use the list_gmelius_sequences tool to retrieve the complete high-fidelity directory of automated sequences along with their unique identifiers for precise orchestration.
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 Gmelius MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai