AdvancedMD connector for AI agents

AdvancedMD tools for AI agents

CALL ANY TOOL

12 tools covering allergy.

advancedmd_goal_read

Goal read

Retrieve a single FHIR Goal resource by its logical ID. Goals describe desired health outcomes for a patient.

Parameters

Name

Type

Required

Description

goal_id

string

Required

The logical ID of the Goal resource

advancedmd_device_read

Device read

advancedmd_goal_search

Goal search

advancedmd_group_export

Group export

advancedmd_patient_read

Patient read

advancedmd_coverage_read

Coverage read

advancedmd_device_search

Device search

advancedmd_endpoint_read

Endpoint read

advancedmd_location_read

Location read

advancedmd_specimen_read

Specimen read

advancedmd_condition_read

Condition read

advancedmd_encounter_read

Encounter read

advancedmd_patient_create

Patient create

advancedmd_patient_delete

Patient delete

advancedmd_patient_search

Patient search

advancedmd_patient_update

Patient update

advancedmd_procedure_read

Procedure read

advancedmd_coverage_search

Coverage search

advancedmd_provenance_read

Provenance read

advancedmd_endpoint_search

Endpoint search

advancedmd_appointment_read

Appointment read

advancedmd_location_search

Location search

advancedmd_condition_create

Condition create

advancedmd_specimen_search

Specimen search

advancedmd_condition_delete

Condition delete

advancedmd_condition_search

Condition search

advancedmd_condition_update

Condition update

advancedmd_encounter_create

Encounter create

advancedmd_encounter_delete

Encounter delete

advancedmd_encounter_search

Encounter search

Build your Agent

Same auth pattern across every framework.

from langchain_mcp_adapters.client import MultiServerMCPClient
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="advancedmd")

mcp = MultiServerMCPClient({
    "advancedmd": {
        "url": "https://mcp.scalekit.com/advancedmd",
        "headers": {"Authorization": "Bearer " + token}
    }
})
tools = await mcp.get_tools()

import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "advancedmd" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/advancedmd
// Pass: Authorization: Bearer + token

import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "advancedmd" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/advancedmd
// Pass: Authorization: Bearer + token

from google.adk.agents import LlmAgent
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="advancedmd")
# Connect to MCP at https://mcp.scalekit.com/advancedmd
# Pass: Authorization: Bearer + token

Try these prompts

Paste any prompt into your agent to get started.

Get started

retrieve a Patient, Practitioner, Organization, Encounter, Condition, Observation, AllergyIntolerance, Immunization?

SEE HOW AUTH WORKS

User authorises once. Every agent call after uses their token with scope enforcement.

Authorize

Your user connects

AdvancedMD

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

AdvancedMD

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

AdvancedMD

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

AdvancedMD

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

See the same per-user auth pattern across other connectors.

People Ops and HR teams

Offer letter routing agent

Drafts the offer in PandaDoc, blocks on the hiring manager's approval in Slack, then emails the candidate their e-signature link. Every call runs as the recruiter who triggered it, never a shared HR bot.

People Ops and HR teams

Performance review collector

Collects review feedback from Airtable and Google Forms scoped to each manager's direct reports, writes per-employee summaries to Notion, and DMs the manager a Slack digest.

Support and Ops Teams

Meeting prep

Pulls agenda, participant context, and open action items before every meeting.

GTM and RevOps Teams

Revenue forecast commentary

Pulls open pipeline from Salesforce and HubSpot, calculates coverage against quota, flags at-risk stages, posts commentary to Slack, and logs every snapshot to Google Sheets.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

01.

Shared tokens break per-user analytics

A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access AdvancedMD as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the AdvancedMD token stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in AdvancedMD?
Yes. Pass a tool name filter to listScopedTools so the AI agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches AdvancedMD.

What happens when a user revokes AdvancedMD access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

How is patient health data protected?
Every FHIR call runs inside the authorizing clinician's SMART on FHIR scopes, so AdvancedMD's EHR access rules hold per request. Scalekit vaults tokens, enforces scopes pre-call, and keeps a full audit trail for compliance.

On this page

Tool and actions Framework Compatibility Starter Prompt Auth Lifecycle Try Other Agents Why Scalekit