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MCP-Powered Health Intelligence

Agent ready context powering
AI native healthcare solutions.

contextRx.ai is a secure marketplace connecting healthcare data providers with AI applications — delivering rich, privacy-preserved context through the Model Context Protocol.

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Claims Cost Reduction
7.5%
Year 1 · 42,000 enrolled members
RCT Validated
Context Variables
10k+
SDoH, clinical, behavioral signals
HIPAA Compliant
Rising-Risk Identification
94%
Precision · Multi-chronic population
HITRUST Certified
HIPAA Architecture
AWS BAA Covered
MCP Native
16 Data Providers
7 MCP Tools
Per-Call Pricing
RCT Validated Outcomes
Zero Raw Data Exposure
01 — How It Works
A secure broker for AI health context.
Providers retain full control of their data. Consumers get seamless, metered access. contextRx.ai handles discovery, authentication, routing, and billing — without ever touching raw patient data.
01 / 04
🏥
Provider Onboarding
Healthcare organizations register their MCP endpoints, define available tools and query types, set usage terms, and publish anonymized metadata to the contextRx.ai registry — all without exposing raw records.
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02 / 04
🤖
Consumer Discovery
AI applications browse a searchable catalog of available context types — filtered by data type, latency, cost, and compliance attributes. Natural language search and ML recommendations surface the right providers instantly.
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03 / 04
🔀
Secure Routing
The contextRx.ai MCP proxy authenticates requests, routes to the appropriate provider server, and intercepts responses for metering. Provider systems execute queries locally and return only processed, aggregate results.
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04 / 04
💳
Usage-Based Economics
Metering tracks API calls, data volume, and compute intensity in real time. Consumers are billed per interaction; providers receive 70% revenue share. Settlements run monthly with transparent dashboards for both sides.
Revenue Share
70%
to providers
02 — Platform
Everything an AI ecosystem needs.
From zero-trust security to real-time metering — contextRx.ai is the infrastructure layer for safe, scalable, and economically fair AI context exchange.
🔒
Privacy by Architecture
PHI transits RAM only during enrichment and is never written to disk or stored in transit. The enrichment engine hashes member identifiers before any external logging. Per-provider consent gates enforce patient authorization before any data is retrieved. Full audit trail in S3 with 7-year KMS-encrypted retention.
HIPAA AWS BAA TLS 1.3 KMS Encrypted Consent Gated Audit Logged
📡
MCP-Native Routing
Built on the open MCP standard. Every interaction uses authenticated, scoped sessions with full stateful support for multi-turn AI agent workflows.
📊
Real-Time Metering
Every MCP call is metered and attributed to the calling provider via Lago. Per-customer spend caps with hard-stop and grace-period modes. Anomaly detection flags unusual burst patterns before they hit billing limits.
🔍
Intelligent Routing
The data router automatically selects the right providers for each capability based on the member's insurance type and coverage population. Primary providers run first, secondary providers fill gaps — all transparent to the calling agent.
⚡
Auto-Scale Infrastructure
EC2 Auto Scaling Group behind an Application Load Balancer — automatically replaces unhealthy instances and scales to demand. CloudFront CDN with global edge caching. Redis-backed response cache with 4-hour TTL reduces provider API calls and latency.
03 — Platform Numbers
Built for production from day one.
The numbers behind the platform — data providers integrated, clinical capabilities available, and the infrastructure running today.
16
Data providers
integrated
7
MCP tools
available today
91
AWS resources
in production
4hr
Member context
cache TTL
Clinical Intelligence
DDI detection, PDC adherence scoring, lab correlation, and composite risk stratification — built into every context response.
Enrichment engine · Runs on every get_member_context call
What Agents Get
✓ Risk score + intervention type on every member context call
✓ Drug interaction flags ranked by severity with recommended actions
✓ Human review trigger with reason codes when confidence is low
04 — Use Cases
Built for every corner of healthcare AI.
From health plan analytics to clinical decision support — contextRx.ai powers the context layer that makes AI agents genuinely useful in healthcare.
🏥
Population Health Management
Identify rising-risk cohorts across multi-chronic populations. Layer SDoH, behavioral, and claims signals to prioritize outreach before costs escalate.
Health Plans · ACOs
🩺
Clinical Decision Support
Give care teams real-time access to whole-person context at the point of care — surfaced via MCP-compatible AI agents embedded in EHR workflows.
Providers · Health Systems
📈
Payer Analytics
Aggregate cross-payer insights while preserving member privacy. Power actuarial models, network optimization, and value-based contract performance tracking.
Payers · Actuaries
🤝
Care Management Agents
AI agents that understand the whole person — not just their last claim. Personalized outreach, coaching recommendations, and barrier identification at scale.
Care Management Programs
🔬
Life Sciences Research
Access privacy-preserved real-world data for study design, cohort identification, and comparative effectiveness research — without complex BAA negotiations.
Pharma · Research Orgs
🏗️
Digital Health Platforms
Enrich your application with verified clinical, behavioral, and SDoH context from a growing marketplace of compliant, metered health data providers.
Digital Health · Startups
05 — How Queries Work
Your agent asks. We figure out the rest.
The platform automatically routes every question to the right query path — member-level or population-level — based on what your agent is asking. No configuration required. No separate endpoints to manage.
👤
Member-Level Queries
Individual context
When your agent asks about a specific member — their medications, risk score, drug interactions, or care gaps — the platform resolves their identity, queries the right providers based on their insurance type, runs the full enrichment pipeline, and returns a structured context package.
→ get_member_context — enriched clinical context, risk score, DDI flags, adherence gaps
→ get_hcp_context — prescribing patterns, payment relationships, NPI profile
→ flag_drug_interactions — severity-ranked DDI analysis with recommended actions
// Agent asks about one member
"What are the medication risks for member 12345?"
→ member-level · 4hr cache · per-call billing
👥
Population-Level Queries
Aggregate analytics
When your agent asks about a cohort or population — risk distribution, adherence trends, intervention opportunities across thousands of members — the platform routes to the analytics engine. No individual PHI is exposed. Results are aggregated, cached for 24 hours, and billed as a single cohort event.
→ get_cohort_brief — risk distribution, top DDI pairs, mean adherence across population
→ compute_cohort_metrics — batched population analytics with 50-member concurrent processing
→ get_intervention_analytics — programme performance, cost reduction attribution
// Agent asks about a population
"Which cohorts are highest risk this quarter?"
→ population-level · 24hr cache · single event billing
The agent never has to choose.
The platform reads the intent of every query and routes it automatically. A natural language question about a specific member triggers the member pipeline. A question about a cohort or trend triggers the population pipeline. Your agent just asks — contextRx handles the rest.
7
MCP tools
2
query paths
0
configuration needed
06 — See It Live
Connect in minutes. See results immediately.
The MCP endpoint is live at https://www.contextrx.ai/mcp. Try the interactive demo to see a real enrichment response — risk scoring, DDI detection, adherence gaps, and intervention recommendations — on synthetic Medicare patients.
Try the Live Demo Get your API key →
07 — Pricing
Pay per call. Scale as you grow.
Simple, transparent, usage-based pricing. No monthly minimums, no hidden fees. Start integrating today and only pay for what your agents use.
Digital Health · Startups
Standard
$0.05
per MCP call · billed monthly
  • All 7 MCP tools
  • 16 data providers
  • Up to 2 requests/second
  • Real-time usage dashboard
  • Sandbox + Synthea test data
  • Email support
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Most Popular
Health Plans · Mid-Market
Professional
$0.03
per MCP call · volume discounts apply
  • Everything in Standard
  • Up to 10 requests/second
  • Spend caps + anomaly alerts
  • CMS Blue Button + BCDA access
  • BAA included
  • Dedicated onboarding support
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Large Payers · PBMs · ACOs
Enterprise
Custom
Volume pricing + dedicated infrastructure
  • Negotiated per-call rates
  • 30 requests/second burst
  • Dedicated AWS infrastructure
  • Custom SLA + uptime guarantee
  • BCDA bulk cohort export
  • White-glove integration support
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See the person.
Predict the risk.
Prove the savings.

Get API access today. Whether you're building AI agents for MTM, care management, or population health — contextRx.ai is the clinical context layer your agents need.

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✓ PHI transits RAM only — never stored in transit
✓ HIPAA-architecture with AWS BAA
✓ MCP-native — connect in under an hour