Bring Medical Appointments
to Pydantic AI
Learn how to connect Doctolib to Pydantic AI and start using 8 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for Subscribers
What is the Doctolib MCP Server?
Connect your Doctolib partner account to any AI agent and take full control of your healthcare scheduling and practitioner research through natural conversation.
What you can do
- Practitioner Discovery — Search for doctors and specialists by specialty and city, identifying bounded office locations and member approximations natively
- Availability Tracking — Identify bounded routing spaces verifying absolute time availability slots attached directly matching the targeted doctor
- Appointment Management — List complex mappings evaluating exactly scheduled times and identifying physical reservations active within your account
- Live Booking — Commands the backend orchestrating real-time database locks inserting explicit reservation parameters structurally binding to an exact time slot
- Visit Motive Identification — Read available reason categories explicitly supported by a given Practitioner required for slot lock verification
- Practice Navigation — Perform structural extraction of localized entity bounds configuring the raw office locations active within the application
- Specialty Mapping — Enumerate explicitly attached structured roles defining valid medical specialties and practitioner targets globally
How it works
1. Subscribe to this server
2. Enter your Doctolib Partner API Key and API URL (e.g., https://api.doctolib.fr)
3. Start managing your healthcare appointments from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Patients — search for specialists and book appointments without navigating the web interface
- Healthcare Coordinators — manage schedules for multiple patients and verify doctor availability in real-time
- Medical Software Vendors — test and debug Doctolib integrations and appointment booking flows through natural conversation
- Administrative Assistants — audit scheduled visits and manage appointment logs using natural language
Built-in capabilities (8)
Consulter le profil d'un praticien
Vérifier les créneaux disponibles pour un praticien
Lister les cabinets médicaux
Lister les rendez-vous pris
Lister toutes les spécialités médicales disponibles
Lister les motifs de consultation d'un praticien
Prendre un rendez-vous médical
Restricts search to explicit city boundaries natively bypassing local lists. Rechercher des praticiens par spécialité et ville
Why Pydantic AI?
Pydantic AI validates every Doctolib tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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 Doctolib 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 Doctolib connection logic from agent behavior for testable, maintainable code
Doctolib in Pydantic AI
Doctolib and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Doctolib 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 Doctolib in Pydantic AI
The Doctolib 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 8 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
Doctolib for Pydantic AI
Every tool call from Pydantic AI to the Doctolib MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can my agent search for specific medical specialists in a city?
Yes. Use the 'rechercher_praticiens' tool. Provide the specialty (e.g., 'médecin généraliste') and the city. The agent will retrieve matching practitioner profiles from Doctolib's active directory natively.
How do I book a consultation slot through the agent?
First, use 'disponibilites' to find free slots for a doctor. Then, provide the practitioner ID, the chosen slot ID, and your email to the 'prendre_rendez_vous' tool to confirm your reservation in the database.
Can I see all medical practices connected to my account?
Absolutely. Use the 'lister_cabinets' tool. Your agent will perform a structural extraction of localized entity bounds, showing you all physical office locations managed within your Doctolib partner environment.
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 Doctolib MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai