Drug discovery and clinical diagnostics run on two languages that rarely speak to each other: lab hardware telemetry and AI reasoning.
Bioassay MCP (seosiri-bioassay-mcp) is a local-first Model Context Protocol server that closes that gap — giving any MCP-compatible AI agent direct access to Sub-Cellular, Cellular, Tissue, and Organism assay math, plus a live conversion path into HL7 FHIR v4.0.1 clinical observations.
A step-by-step developer guide to the bioassay MCP server: High-Throughput Screening (HTS) automation, organoid penetration modeling, and medical device-to-EHR telemetry, built for AI agents that need to reason over real lab data.
Lead Architect: Momenul Ahmad | Organization: SEOSiri-Official | Package: PyPI · seosiri-bioassay-mcp v1.1.1 | Directory: SEOSiri MCP Server Hub
On this page
- The biological hierarchy segment engine
- Medical device telemetry & HL7 FHIR integration
- Core tool inventory (10 tools)
- Assay kit comparison: TR-FRET vs UA-Glo vs ELISA vs HICA
- Synergy with the SEOSiri MCP ecosystem
- Step-by-step installation guide
- Custom MCP development for your team
- Executive summary
- FAQ
1. The Biological Hierarchy Segment Engine
Biotechnology research spans multiple organizational tiers — from molecular ligand-receptor interactions up to whole-organism pharmacokinetics. As a bioassay MCP server, seosiri-bioassay-mcp structures every calculation across four distinct biological segments, so an AI agent can move between scales without switching tools:
- Sub-Cellular Tier: TR-FRET emission ratio math (665nm / 620nm) for target engagement assays, including PROTAC ternary complexes (BRD4/CRBN, DDB1-CRBN & GSPT1), KRAS variants (WT vs G12C/cRAF), and receptor-ligand binding (TNF-α/TNFR, IL family).
- Cellular Tier: UA-Glo luminescent functional screening for 2D/3D cell viability, Caspase 3/7 apoptosis, kinase activity, and reporter gene activation (NF-κB, Wnt pathways).
- Tissue Tier: 3D organoid and spheroid penetration models evaluating core-to-surface drug diffusion ratios and tissue slice permeability.
- Organism Tier: In vivo pharmacokinetics — total administered dose, maximum plasma concentration (Cmax), elimination half-life (t1/2), and Area Under the Curve (AUC).
2. Medical Device Telemetry & HL7 FHIR Integration
Beyond assay mathematics, the server behaves as a Medical Device Data System (MDDS). It ingests raw telemetry from clinical laboratory hardware — microplate readers, spectrophotometers, blood gas analyzers — and automatically converts each measurement into a compliant HL7 FHIR v4.0.1 Observation JSON resource for sync with hospital EHR systems such as Epic and Cerner, enforcing HIPAA PII/PHI anonymization at the edge before any data leaves the device.
3. Core Tool Inventory (10 Multi-Segment Tools)
The bioassay MCP server exposes 10 production-tested tools to any connected AI agent:
- calculate_tr_fret_ratio — HTRF 665nm/620nm ratio processing for PROTAC, KRAS, and cAMP assays.
- analyze_uaglo_luminescence — RLU luminescence analysis for 2D/3D viability, apoptosis, and reporter genes.
- quantify_onestep_elisa — 1-hour fast ELISA biomarker concentration calculations (IL-2, IL-6, IFN-γ, IgG, TSH).
- analyze_hica_fluorescence — ultra-sensitive fluorescence analysis for low-abundance proteins (IL-2R, IL-8, IL-12p70).
- calculate_tissue_organoid_penetration — 3D spheroid core-to-surface drug diffusion depth models.
- calculate_organism_in_vivo_pharmacokinetics — whole-organism dosing, clearance, and AUC decay.
- generate_plate_layout — automated 96-well / 384-well microplate layout generator with segment tagging.
- get_assay_kit_specifications — protocol query engine for TR-FRET, UA-Glo, ELISA, and HICA kit sizing.
- ingest_medical_device_telemetry — raw hardware telemetry ingestor with automated calibration checks.
- convert_to_fhir_observation — converts assay measurements into HL7 FHIR v4.0.1 Observation JSON resources.
To inspect source code, commits, or open a pull request, visit the official repositories on GitHub, GitLab, or the ActiveState Platform.
4. Assay Kit Comparison: TR-FRET vs UA-Glo vs ELISA vs HICA
A quick reference for choosing which tool and kit protocol fits your bioassay MCP workflow:
| Kit / Method | Biological Tier | Best For | MCP Tool |
|---|---|---|---|
| TR-FRET (HTRF) | Sub-Cellular | PROTAC ternary complexes, KRAS, cAMP | calculate_tr_fret_ratio |
| UA-Glo (Luminescence) | Cellular | 2D/3D viability, apoptosis, reporter genes | analyze_uaglo_luminescence |
| 1-Step ELISA | Cellular / Clinical | Fast biomarker quantification (IL-2, IL-6, TSH) | quantify_onestep_elisa |
| HICA Fluorescence | Cellular / Clinical | Ultra-low-abundance protein detection | analyze_hica_fluorescence |
5. Synergy with the SEOSiri MCP Ecosystem
In life-sciences and HTS pipelines, the bioassay MCP server operates in tandem with other SEOSiri-Official servers:
- Bio-Robotics Core (seosiri-biorobotics) — translates genomic sequence queries (UniProt) and surface EMG biosignals into safe, Cartesian G-code coordinates for automated liquid-handling gantries.
- ETL Data Pipeline (etl-pipeline-mcp) — ingests high-velocity webhooks, executes SHA-256 PII scrubbing, stitches customer identities across platforms, and exports clean analytical buffers to Snowflake, ClickHouse, or BigQuery.
- API Guard (seosiri-api-guard) — rate-limiting and schema-validation gateway for securing MCP tool calls in production.
- Learning Orchestrator (seosiri-learning-orchestrator) — sequences multi-step AI agent learning and evaluation workflows across connected MCP tools.
See the full roster on the SEOSiri MCP Server Directory.
6. Step-by-Step Installation Guide
Choose the path that matches your environment. All three are verified and reproducible.
Option A — Direct PyPI Installation
Install the latest stable release (currently v1.1.1) straight from PyPI:
pip install seosiri-bioassay-mcp
Option B — Reproducible Runtime via the ActiveState Platform
For a fully locked, cross-platform runtime with a verified build history, deploy through platform.activestate.com/seosiri/bioassay-mcp. Pick your target OS, then run the matching install commands:
Windows 10 (64-bit)
- Download the ActiveState CLI tool and run
state-remote-installer.exein Command Prompt. - Check out the locked runtime:
state checkout seosiri/bioassay-mcp .
macOS 11+ and Linux (Glibc 2.28), 64-bit
- Install the ActiveState CLI in Terminal:
curl -fsSL https://platform.activestate.com/dl/cli/_pdli02/install.sh | sh
- Check out the locked runtime:
state checkout seosiri/bioassay-mcp .
Option C — Zero-Setup Execution via uv (Claude Desktop / Cursor)
To run the MCP server directly from GitHub with no global dependencies, add this to your claude_desktop_config.json:
{
"mcpServers": {
"seosiri-bioassay": {
"command": "uv",
"args": [
"run",
"--github",
"SEOSiri-Official/bioassay-mcp",
"src/main_server.py"
]
}
}
}
Cloudflare Edge Gateway: prefer a hosted endpoint over local install? Route requests through the live Cloudflare Worker gateway at
bioassay.seosiri.com — no runtime setup required.
7. Custom MCP Development for Biotech, CROs & Device Manufacturers
Beyond the open-source release, SEOSiri provides dedicated technical consulting, custom MCP architecture, and hardware-to-agent deployment services for biotech firms, clinical research organizations (CROs), and medical device manufacturers:
- Custom Clinical Hardware Connectors — connecting microplate readers, spectrophotometers, and blood gas analyzers directly to local or cloud-hosted AI agents.
- HL7 FHIR & EHR Integration — building compliant observation converters that push lab findings straight to hospital networks (Epic, Cerner).
- Enterprise AI Compliance Auditing — implementing custom PII/PHI scrubbing policies so AI agent workflows meet HIPAA and GDPR standards.
To discuss a custom bioassay MCP build or B2B pipeline engineering, reach out directly:
- Website: seosiri.com
- MCP Directory: seosiri.com/2026/07/seosiri-mcp-servers.html
- Enterprise Support: admin@seosiri.com
- GitHub Sponsors: Sponsor SEOSiri-Official
Executive Summary
seosiri-bioassay-mcp is a local-first, multi-tier bioassay MCP server for high-throughput screening and clinical lab automation:
- Hierarchy Engine: processes assay math across Sub-Cellular, Cellular, Tissue, and Organism tiers.
- Clinical EHR Integration: converts lab measurements directly into HL7 FHIR v4.0.1 Observation resources.
- Cloudflare Edge Gateway: deployed via Cloudflare Workers (bioassay.seosiri.com) for low-latency global routing.
- Cross-Platform: verified deployment on Windows 10, macOS 11+, and Linux (Glibc 2.28), all 64-bit.
Query Answers
Question: What is seosiri-bioassay-mcp?
Answer: seosiri-bioassay-mcp is an open-source Model Context Protocol server built by SEOSiri to connect AI agents with High-Throughput Screening (HTS) assay math, clinical lab device telemetry, and HL7 FHIR observation conversions.
Question: Which biological tiers are supported by the bioassay MCP server?
Answer: Four tiers — Sub-Cellular (PROTAC, KRAS, receptors), Cellular (2D/3D viability, apoptosis, kinases), Tissue (spheroid/organoid penetration), and Organism (in vivo pharmacokinetics).
Question: How does the server integrate with medical devices and clinical EHR systems?
Answer: It ingests raw telemetry from microplate readers, spectrophotometers, and blood gas analyzers, automatically formatting measurements into HL7 FHIR v4.0.1 Observation resources with anonymized patient references for EHR sync.
Question: How do I install seosiri-bioassay-mcp?
Answer: Run pip install seosiri-bioassay-mcp, or deploy a locked runtime through the ActiveState Platform — state-remote-installer.exe on Windows, or the curl install.sh script on macOS/Linux — then run state checkout seosiri/bioassay-mcp .
Question: Is seosiri-bioassay-mcp free and open source?
Answer: Yes — it's MIT-licensed, free on PyPI, and the source is public on GitHub and GitLab.
