📌 Key Takeaways: SEOSiri MCP Ecosystem
- Decoupled Architecture: Separating high-level AI agent reasoning from physical hardware execution and compliance logic prevents system-level fragility and eliminates restrictive vendor lock-in.
- Multi-Disciplinary Scope: A cohesive ecosystem capable of managing bioinformatics gantry coordinates, clinical HIPAA privacy, financial PCI-DSS checksums, GDPR/SEO structural metadata, spaced repetition, and mobile biometric IoT authentication under unified schemas.
- Sovereign Offline Autonomy: Local-first configurations (utilizing in-memory SQLite and local models via Ollama) allow complete workflows to run entirely offline, bypassing regional network proxies, latency, and cloud API timeouts.
- Cryptographic Policy Enforcement: The introduction of an independent "Policy Plane" (Sovereign Policy Interceptor) cryptographically signs (HMAC-SHA256) valid trajectories, blocking unauthorized or spastic hardware commands directly on-device.
👨💻 Lead Architect & Open-Source Attribution
This unified Model Context Protocol (MCP) ecosystem is designed and engineered by Momenul Ahmad, Lead Architect and Founder of SEOSiri.
All five core systems are maintained under the official SEOSiri-Official open-source research initiative. To support active bionics kinematics, security research, or hardware lab testing, consider supporting the team via the SEOSiri GitHub Sponsors Portal.
As autonomous AI agents (such as Claude Code, Cursor, and custom enterprise agents) evolve, their role is shifting from basic text generation to direct system actuation. Today, AI agents are being tasked with writing code, querying external APIs, managing database pipelines, and even generating mechanical movements.
However, this autonomy introduces significant security, safety, and compliance liabilities. If an AI agent has direct access to system layers, how do we prevent credential leakage, database injection, or uncalibrated mechanical movements that could damage physical laboratory hardware or bionic limb assemblies?
To resolve these integration challenges, SEOSiri-Official has open-sourced a suite of **five modular, local-first MCP servers**. By decoupling high-level AI reasoning from physical execution, we establish a secure, auditable, and deterministic translation layer.
The SEOSiri Open-Source MCP Directory
Our complete suite is open-source under the MIT License, fully verified via automated CI/CD pipelines on GitHub Actions, and globally indexed on the official Glama Registry:
| Server Repository | Primary Architectural Role | Exposed Tools |
|---|---|---|
| biorobotics | Actuation Core: Converts biological sequence parameters and EMG signals to G-code [3]. | fetch_genomic_data, resolve_biotech_spatial_intent, map_plate_coordinate, calculate_pipetting_speed, calculate_dna_melting_temp, translate_emg_to_actuation |
| seosiri-api-guard-mcp-server | Security Proxy: OWASP scanner and multi-profile compliance interlock with cryptographic signatures. | sanitize_and_validate_payload (OWASP, HIPAA, PCI-DSS, GDPR, Biorobotics Interlock) |
| lambda-data-pipeline-mcp | Analytics Engine: Ingests webhooks and CRM batches into Hot/Cold storage with ID stitching. | ingest_realtime_webhook, ingest_batch_api_poll, process_lambda_pipeline, export_to_data_warehouse, retrieve_analytical_summary |
| learning-orchestrator-mcp | Pedagogical Brain: Manages syllabi, Bloom's tests, SuperMemo SM-2 spacing, and LMS SCORM sync. | get_progressive_syllabus, generate_skills_assessment, calculate_spaced_repetition, sync_ai_platform_state, sync_lms_onboarding_state |
| biometric-iot-bridge-mcp | Mobile HMI Proxy: Verifies Flutter FaceID tokens over MQTT with 5-min temporal locks. | secure_biometric_iot_gatekeeper |
1. Biorobotics Actuation Core (`seosiri-biorobotics`)
The seosiri-biorobotics engine translates abstract biological research into physical coordinates represented strictly in International System (SI) units (meters). These coordinates are then formatted as standardized Cartesian G-code commands (RS-274/NGC standard) used by standard CNC gantries, automated liquid handlers, and bionic joint servos.
- UniProt REST Integration: Fetches live open-access sequence parameters (e.g., GFP
P42212or Human InsulinP01308), falling back gracefully to local reference data when offline. - SLAS/SBS 96-Well Plate Mapping: Converts alphanumeric well IDs (e.g.,
B5) into physical millimeter offsets based on standard 9.0 mm pitch spacing. - Viscosity-Based Feedrate Calibration: Dynamically calculates safe G-code movement speeds (F-values) and pressure stabilization delays based on fluid viscosity in Centipoise (cP) to prevent pipetting cavitation.
- Biological Thermodynamics: Analyzes DNA sequence GC-content to determine melting temperatures ($T_m$) and output target deck bed heating offsets.
- Surface EMG Bionics Translation: Translates human muscle electrical signals (0–1000 µV) into safe $0^\circ\text{--}180^\circ$ joint angles, applying an active velocity clamp when high tension (>700 µV) is detected to prevent mechanical spasms.
2. Sovereign Security Proxy (`seosiri-api-guard-mcp-server`)
Operating as an independent "Policy Plane," the API Guard intercepts proposed LLM payloads before they touch external networks or hardware buses.
- Universal OWASP Core: Scans for SQL injections, shell command executions, and path traversal strings.
- Healthcare Profile (HIPAA/FHIR): Automatically scrubs PII/PHI (Social Security Numbers, Dates of Birth) from outgoing contexts.
- Fintech Profile (PCI-DSS):** Scans for credit card Primary Account Numbers (PAN) using the Luhn algorithm and redacts them in transit.
- Biorobotics Safety Interlock: Recursively parses nested JSON payloads containing G-code, verifies coordinates against physical deck limits ($200\text{mm} \times 150\text{mm} \times 100\text{mm}$), clamps unsafe coordinates, and generates an HMAC-SHA256 signature required by the serial driver.
3. Event-Driven Lambda Analytics (`lambda-data-pipeline-mcp`)
Designed to process high-volume streams without exceeding LLM context token windows, this server implements a two-tier storage model:
- Hot Tier (RAM): High-speed in-memory queueing for real-time webhooks with active backpressure control (throttling if queue exceeds 10,000 items).
- Cold Tier (Disk):** On-disk SQLite database (`cold_storage.db`) storing historical records. During migration, the server executes **Identity Stitching**—linking social IDs, CRM lead IDs, and emails under a single `mcp_root_id`—and hashes raw emails using SHA-256 for GDPR compliance at rest.
- Warehouse Exporters: Serializes anonymized historical records directly into export buffers formatted for enterprise data warehouses (Snowflake, ClickHouse, BigQuery).
4. Pedagogical Brain (`learning-orchestrator-mcp`)
Replaces un-structured AI tutoring with deterministic educational standards:
- Bloom's Taxonomy Assessment Generator: Generates targeted evaluation questions mapped to cognitive dimensions (Remembering, Applying, Analyzing).
- SuperMemo SM-2 Spaced Repetition Engine: Calculates optimal review dates based on user recall grades (0–5 scale) and ease factors, using timezone-aware UTC objects to prevent runtime deprecation warnings.
- LMS LTI/SCORM Sync Bridge: Consumes raw SCORM quiz scores from corporate platforms (like Moodle or Canvas), maps them to SM-2 quality grades, and outputs cryptographically signed LTI Outcomes payloads.
5. Mobile Biometric IoT Proxy (`biometric-iot-bridge-mcp`)
Connects native mobile hardware security directly to AI agents:
- Flutter Integration: Cryptographically links with our published open-source Flutter package biometric_iot_bridge, (Read the full Biometric IoT Bridge Research Publication) [1.2.0].
- Temporal & Anti-Replay Guard: Enforces a strict 5-minute (300-second) transaction window and maintains a local memory registry of processed signature hashes, blocking replay attacks before authorizing physical G-code actuation.
A Technical Note on Glama.ai Registry Metrics
When developers view newly published repository cards on Glama, they may observe that the Server Coherence and Tool Definition Quality metrics are displayed as gray pending circles, and the Windows/macOS/Linux compatibility badges are temporarily absent.
This is standard behavior. Glama.ai executes code quality, server coherence, and multi-platform compatibility scans asynchronously via a background queue. Once the remote container finishes its scheduled run, these metrics automatically update to verified green A ratings, and the platform compatibility badges render on the card.
🔌 Developer's Guide: How to Connect your AI Clients
You can connect our servers to your local AI clients (such as Claude Desktop or Cursor IDE) using one of two standard methods.
Method 1: Direct Execution from GitHub (Zero-Setup, Recommended)
If you have the Python package manager uv installed, configure your claude_desktop_config.json to run our servers directly from GitHub without cloning:
{
"mcpServers": {
"seosiri-data-pipeline": {
"command": "uv",
"args": [ "run", "--github", "SEOSiri-Official/lambda-data-pipeline-mcp", "src/main_server.py" ]
},
"seosiri-api-guard": {
"command": "uv",
"args": [ "run", "--github", "SEOSiri-Official/seosiri-api-guard-mcp-server", "src/main_server.py" ]
},
"seosiri-learning-orchestrator": {
"command": "uv",
"args": [ "run", "--github", "SEOSiri-Official/learning-orchestrator-mcp", "src/main_server.py" ]
},
"seosiri-biometric-iot": {
"command": "uv",
"args": [ "run", "--github", "SEOSiri-Official/biometric-iot-bridge-mcp", "src/main_server.py" ]
}
}
}Method 2: Local Execution (If Cloned)
If you have cloned a repository locally, point your client configuration directly to your entry script:
{
"mcpServers": {
"seosiri-data-pipeline": {
"command": "python",
"args": [ "D:/lambda-data-pipeline-mcp/src/main_server.py" ],
"env": { "PYTHONPATH": "D:/lambda-data-pipeline-mcp" }
}
}
}Queries
Question: What is the SEOSiri Model Context Protocol (MCP) Ecosystem?
Answer: The SEOSiri MCP Ecosystem is an open-source suite of five specialized Model Context Protocol servers engineered by Momenul Ahmad. It covers bio-robotic kinematics, multi-industry API security, Lambda big data ingestion, AI-driven pedagogy, and mobile biometric IoT authentication.
Question: How does the SEOSiri API Guard protect physical robotic controllers?
Answer: The API Guard acts as an independent 'Policy Plane'. It scans proposed G-code movement commands against hard boundaries, applies velocity clamps to prevent splashing, and generates an HMAC-SHA256 signature. The physical serial driver rejects any command lacking this verified signature.
Question: How does the Biometric IoT Bridge link Flutter mobile apps to physical actuators?
Answer: The biometric_iot_bridge Flutter package authenticates users via FaceID or Fingerprint on iOS/Android [2]. It derives a rolling HMAC-SHA256 token and broadcasts it over MQTT. The SEOSiri Biometric MCP Server receives the token, enforces a 5-minute temporal window, runs anti-replay checks, and authorizes physical G-code actuation.
Question: Why are SEOSiri's MCP servers designed as local-first systems?
Answer: Designing our servers to run locally ensures absolute user privacy, zero network latency, and operational independence. It allows laboratories and researchers to run automated assays entirely offline using local AI engines (like Ollama), bypassing regional network proxies or cloud connection timeouts.
Question: How does the SEOSiri Lambda Data Pipeline execute Identity Stitching and GDPR compliance simultaneously?
Answer: The pipeline ingests high-velocity webhooks into an in-memory Hot Tier (RAM) and schedules batch CRM polls to an on-disk Cold Tier (Disk). During migration, the identity stitching engine hashes sensitive email identifiers using SHA-256 and merges different user handles under a single anonymous mcp_root_id, ensuring no raw PII is stored at rest.
Question: Can I deploy SEOSiri's MCP servers on Windows, macOS, or Linux?
Answer: Yes. All five MCP servers are built using cross-platform Python. They are fully compatible with Windows, macOS (Apple), and Linux. You can run them directly over the standard input/output (stdio) transport layer or deploy them inside lightweight Docker containers on your local machine or local network.
Question: How does the Spaced-Repetition Engine in the Learning Orchestrator calculate review dates?
Answer: It implements the mathematically verified SuperMemo SM-2 algorithm. It processes a student's quality of recall grade on a 0-to-5 scale, adapts their cognitive ease factor, and calculates the exact next review date using timezone-aware UTC datetimes to eliminate runtime deprecation warnings.
Question: Why are platform badges (Windows, Apple, Linux) temporarily showing as pending on new Glama listings?
Answer: Glama.ai executes code quality, server coherence, and multi-platform compatibility scans asynchronously in a background runner queue. Once a newly published container release finishes its scheduled scan, these scores automatically update to green 'A' ratings and render the OS platform icons.
💼 B2B Custom Solutions & Systems Integration Services
To support enterprise scaling, SEOSiri-Official offers specialized, high-ticket systems-integration consulting and custom software development across Linux, Windows, and macOS (Apple) environments:
- Custom Laboratory Actuation: Designing multi-axis Cartesian gantries, closed-loop optical feedback loops, and capacitive liquid-level sensors for industrial pipetting platforms (e.g., Tecan, Hamilton, Opentrons).
- Bespoke Enterprise API Security: Deploying locked, proprietary compliance profiles (SOC2 Type II, ISO-27001, and custom PHI/PII masking rules) inside secure, on-premise container networks.
- Enterprise Big Data & Warehouse Exports: Customizing high-velocity webhook ingestion streams and configuring automated identity stitching feeds directly into corporate Snowflake, ClickHouse, or BigQuery instances.
- Mobile Biometric Hardware Relays: Connecting our open-source biometric_iot_bridge Flutter Package directly to your secure on-premise hardware relays, smart locks, or industrial machinery.
To discuss your industrial hardware configurations, API security audits, or custom compliance profiles, contact our systems architecture team directly:
Official Website: seosiri.com
Enterprise Support Email: [email protected]
⚠️ Safety & Regulatory Note
All bionics, robotics, and security-compliance tools are designed as reference implementations suitable for prototyping, educational research, and simulation. Any clinical deployment, automated diagnostic execution, or assistive prosthetic integration requires independent regulatory validation beyond the scope of these open-source repositories.
