GTH in Action — Real-World Workflows
How admissions consultants, treatment center operators, and researchers use GTH’s MCP server to get structured facility intelligence in seconds.
Admissions Consultant — Market Research
Scenario: A behavioral health admissions consultant needs to find appropriate treatment options for a client in Nashville, TN who has Cigna insurance and needs residential detox.
Ask Claude or ChatGPT
“Find detox centers in Nashville, TN that accept Cigna insurance”
GTH Returns:
→ 8 licensed detox facilities in Nashville, TN
→ 5 accept Cigna: Cumberland Heights, Centerstone, Vanderbilt Psychiatric Hospital, Bradford Health Services, Foundations Recovery Network
→ Distance, phone, levels of care, and additional insurance accepted for each
Time saved: What used to take 45 minutes of manual SAMHSA lookup and phone calls takes under 10 seconds.
Treatment Center Operator — Competitive Intelligence
Scenario: The admissions director at a Chicago IOP facility wants to understand their competitive landscape — specifically which nearby competitors accept Medicaid that they currently don’t.
Ask Claude or ChatGPT
“Show me the 5 nearest IOP programs to zip code 60601 and which ones accept Medicaid”
GTH Returns:
→ 5 nearest IOP facilities to 60601 with distances (0.4mi to 2.1mi)
→ 3 of 5 accept Medicaid: Gateway Foundation, Haymarket Center, TASC
→ 2 of 5 do not accept Medicaid: [competitor names]
→ Full insurance lists and service offerings for each
Follow-up prompt: “Which insurance plans do all 5 accept that I don’t currently accept?” — GTH cross-references the lists and surfaces the gap instantly.
Behavioral Health Researcher — Market Mapping
Scenario: A healthcare policy researcher needs to map MAT (Medication-Assisted Treatment) availability across rural states to identify coverage gaps for a report on opioid treatment access.
Ask Claude or ChatGPT
“How many MAT programs are available in Wyoming, Montana, and North Dakota? Compare their insurance acceptance rates.”
GTH Returns:
→ Wyoming: 12 MAT programs (8 accept Medicaid, 4 private pay only)
→ Montana: 19 MAT programs (14 accept Medicaid, 5 private pay only)
→ North Dakota: 9 MAT programs (6 accept Medicaid, 3 private pay only)
→ Medicaid acceptance rate: WY 67%, MT 74%, ND 67%
→ Full facility list with addresses and phone numbers for each state
What this replaces: Manual SAMHSA DASIS data exports, spreadsheet cleanup, and hours of cross-referencing state Medicaid directories.
EHR Developer — Facility Data Integration
Scenario: A developer building a behavioral health EHR needs a reliable, structured facility dataset for their referral module — specifically to show which facilities near a patient accept their insurance.
API Query
POST https://gth-mcp-server.pages.dev/mcp
X-GTH-API-Key: gth_live_...
{
"tool": "search_facilities",
"arguments": {
"zip": "37201",
"radius_miles": 25,
"treatment_type": "IOP",
"insurance": "Aetna"
}
}
Returns structured JSON:
→ Array of matching facilities with name, address, phone, distance
→ Insurance accepted (full list per facility)
→ Levels of care offered
→ SAMHSA certification status
Why GTH vs. building your own: 12,373 facilities, cleaned and enriched, updated monthly. Skips 3–4 months of SAMHSA API wrangling and data cleanup.
Ready to connect GTH to your AI workflow?
Free public endpoint available now. Paid plans with dedicated API keys start at $99/mo.