Compatible with every major AI agent and IDE
What is the SAMHSA Treatment Locator MCP Server?
Connect to the SAMHSA Treatment Locator and empower your AI agent to find critical healthcare resources across the United States. This server provides direct access to the official Substance Abuse and Mental Health Services Administration database.
What you can do
- Geographic Search — Find facilities using precise latitude and longitude coordinates within a customizable radius.
- Service Filtering — Narrow down results using specific service codes to find the exact type of care needed (e.g., detox, inpatient, outpatient).
- Detailed Facility Profiles — Retrieve comprehensive metadata for specific facilities, including contact information and available services via unique identifiers.
- Service Code Discovery — Access the full list of available service categories and codes to refine your searches effectively.
How it works
- Subscribe to this server
- Enter your SAMHSA API Key
- Start locating treatment centers from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Healthcare Coordinators — quickly identify nearby treatment options for patients based on specific clinical needs.
- Public Health Researchers — analyze the distribution of mental health and substance use services in specific regions.
- Social Workers — find and inspect facility details directly from their workflow tools to assist clients faster.
Built-in capabilities (3)
Get detailed information for a specific facility
List available service codes used for filtering
Search for treatment facilities based on location and filters
Why Pydantic AI?
Pydantic AI validates every SAMHSA Treatment Locator tool response against typed schemas, catching data inconsistencies at build time. Connect 3 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 SAMHSA Treatment Locator 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 SAMHSA Treatment Locator connection logic from agent behavior for testable, maintainable code
SAMHSA Treatment Locator in Pydantic AI
SAMHSA Treatment Locator and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect SAMHSA Treatment Locator 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 SAMHSA Treatment Locator in Pydantic AI
The SAMHSA Treatment Locator 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 3 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
SAMHSA Treatment Locator for Pydantic AI
Every tool call from Pydantic AI to the SAMHSA Treatment Locator MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I search for treatment facilities near a specific set of coordinates?
Use the search_facilities tool by providing the lat (latitude) and lon (longitude) parameters. You can also specify a radius in miles to define the search area.
Where can I find the list of service codes to filter my search?
You can run the list_services tool. It will return all available service categories and their corresponding codes which you can then use in the service_code parameter of search_facilities.
Can I get the full contact information for a specific facility if I have its ID?
Yes! Use the get_facility tool with the facility_id. This will retrieve detailed information including the address, phone number, and the full list of services provided by that location.
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 SAMHSA Treatment Locator 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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