SEOSiri-Official maintains 15 sovereign, open-source Model Context Protocol (MCP) servers that let AI agents safely act on lab hardware, security policy, clinical assay data, big-data pipelines, knowledge graphs, incident response, and AI-native SEO/AEO/GEO signals — all local-first, MIT-licensed, and cross-platform.
📌 Key Takeaways: SEOSiri MCP Ecosystem
- Fifteen Decoupled Servers: Separating high-level AI agent reasoning from physical hardware execution, compliance logic, knowledge graph engineering, database access, incident response, and search-visibility auditing prevents system-level fragility and eliminates vendor lock-in.
- Multi-Disciplinary Scope: A single ecosystem now manages bioinformatics gantry coordinates, clinical HIPAA/FHIR data, financial PCI-DSS checksums, GDPR structural metadata, AI-native search governance, and mobile biometric IoT authentication under unified schemas.
- Sovereign Offline Autonomy: Local-first configurations (in-memory SQLite, local models via Ollama) allow complete workflows to run entirely offline, bypassing regional network proxies, latency, and cloud API timeouts.
- Cryptographic Policy Enforcement: An independent "Policy Plane" (Sovereign Policy Interceptor) cryptographically signs (HMAC-SHA256) valid trajectories, blocking unauthorized 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 fifteen 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, auditing search visibility, 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, unaudited crawler access, 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 **fifteen modular, local-first MCP servers**. By decoupling high-level AI reasoning from physical execution, compliance, knowledge graph engineering, and search governance, we establish a secure, auditable, and deterministic translation layer.
The SEOSiri Open-Source MCP Directory (15 Servers)
Our complete suite is open-source under the MIT License, verified via automated CI/CD pipelines on GitHub Actions, and published to PyPI. All fifteen have public GitHub repositories; most are also indexed on the Glama Registry. Servers are grouped below by architectural role:
| Server | Category | Primary Role |
|---|---|---|
| Lab Automation & Hardware Security | ||
| biorobotics | Actuation Core | Converts biological sequence parameters and EMG signals to G-code. |
| seosiri-api-guard-mcp-server | Security Proxy | OWASP scanner and multi-profile compliance interlock with cryptographic signatures. |
| biometric-iot-bridge-mcp | Mobile HMI Proxy | Verifies Flutter FaceID tokens over MQTT with 5-minute temporal locks. |
| Big Data, Database & Cloud Infrastructure | ||
| lambda-data-pipeline-mcp | Analytics Engine | Ingests webhooks and CRM batches into Hot/Cold storage with ID stitching. |
| etl-pipeline-mcp | MCP-Native ETL | Hot/Cold tiering, PII scrubbing, Parquet buffers, and warehouse exports. |
| seosiri-db-infra-mcp | DB & Cloud Infra Bridge | Read-only Postgres querying, schema inspection, AWS S3 and Cloudflare audits. |
| Bioscience & Clinical | ||
| seosiri-bioassay-mcp | HTS Assay Engine | TR-FRET/UA-Glo/ELISA/HICA assay math and HL7 FHIR observation conversion. |
| AI-Native SEO, AEO & GEO Governance | ||
| seosiri-aeo-geo-mcp | AI Visibility Auditor | /llm.txt and security.txt auditing plus AEO answer-card extraction. |
| seosiri-keyword-cluster-mcp | Semantic Intelligence | Keyword clustering, intent classification, and cannibalization detection. |
| seosiri-content-schema-mcp | Schema Engineering | Multi-entity JSON-LD generation with GA4 metric validation. |
| seosiri-dns-sec-audit-mcp | DNS & TLS Auditor | DNS record, SOA health, SSL/TLS, and HTTP header audits. |
| seosiri-search-governance-mcp | Crawl Governance | robots.txt enforcement for AI crawlers and real-time IndexNow dispatch. |
| seosiri-semantic-entity-mcp | Knowledge Graph Engine | Named entity extraction, Wikidata disambiguation, and RDF triple construction. |
| Enterprise Operations & Incident Response | ||
| seosiri-ops-comm-mcp | Incident Response Bridge | Sentry error triage, Linear issue sync, and Slack incident dispatch. |
| AI-Driven Pedagogy | ||
| learning-orchestrator-mcp | Pedagogical Brain | Manages syllabi, Bloom's tests, SuperMemo SM-2 spacing, and LMS sync. |
Group 1 · Lab Automation & Hardware Security
1. Biorobotics Actuation Core (`seosiri-biorobotics`)
Translates abstract biological research into physical coordinates in International System (SI) units, formatted as standardized Cartesian G-code (RS-274/NGC) for 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 to local reference data when offline. - SLAS/SBS 96-Well Plate Mapping: Converts alphanumeric well IDs into physical millimeter offsets at 9.0 mm pitch spacing.
- Viscosity-Based Feedrate Calibration: Calculates safe G-code movement speeds from fluid viscosity (cP) to prevent pipetting cavitation.
- Surface EMG Bionics Translation: Translates muscle electrical signals (0–1000 µV) into safe 0°–180° joint angles, clamping velocity when high tension (>700 µV) is detected.
Verified tools: fetch_genomic_data, resolve_biotech_spatial_intent, map_plate_coordinate, calculate_pipetting_speed, calculate_dna_melting_temp, translate_emg_to_actuation.
2. Sovereign Security Proxy (`seosiri-api-guard-mcp-server`)
Operates as an independent "Policy Plane," intercepting 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).
- Fintech Profile (PCI-DSS): Scans for credit card Primary Account Numbers using the Luhn algorithm and redacts them in transit.
- Biorobotics Safety Interlock: Parses nested G-code payloads, verifies coordinates against deck limits (200mm × 150mm × 100mm), clamps unsafe values, and signs valid trajectories with HMAC-SHA256.
Verified tool: sanitize_and_validate_payload (multi-profile: OWASP, HIPAA, PCI-DSS, GDPR/AEO, Biorobotics Interlock).
3. Mobile Biometric IoT Proxy (`biometric-iot-bridge-mcp`)
Connects native mobile hardware security directly to AI agents.
- Flutter Integration: Cryptographically links with the open-source Flutter package biometric_iot_bridge (read the full Biometric IoT Bridge Research Publication).
- Temporal & Anti-Replay Guard: Enforces a strict 5-minute transaction window and maintains a local registry of processed signature hashes, blocking replay attacks before authorizing G-code actuation.
Verified tool: secure_biometric_iot_gatekeeper.
Group 2 · Big Data, Database & Cloud Infrastructure
4. Event-Driven Lambda Analytics (`lambda-data-pipeline-mcp`)
Processes high-volume streams without exceeding LLM context token windows using a two-tier storage model:
- Hot Tier (RAM): High-speed in-memory queueing for real-time webhooks with backpressure control above 10,000 queued items.
- Cold Tier (Disk): On-disk SQLite storing historical records. During migration, Identity Stitching links social IDs, CRM lead IDs, and emails under a single
mcp_root_id, hashing raw emails with SHA-256 for GDPR compliance at rest. - Warehouse Exporters: Serializes anonymized records into export buffers for Snowflake, ClickHouse, and BigQuery.
Verified tools: ingest_realtime_webhook, ingest_batch_api_poll, process_lambda_pipeline, export_to_data_warehouse, retrieve_analytical_summary.
5. MCP-Native ETL System (`etl-pipeline-mcp`)
A companion sovereign ETL system published directly to PyPI, purpose-built for teams who want the Hot/Cold tiering and compliance model without cloning a GitHub repository.
- Hot/Cold Tiering: In-memory ingestion promoted to on-disk cold storage on a schedule.
- Automated PII Scrubbing: Strips sensitive identifiers before persistence.
- Parquet Buffers: Serializes records into columnar Parquet format for efficient downstream analytics.
- Warehouse Exports: Ships clean, anonymized data to enterprise warehouses.
Sovereign Data Engineering: The SEOSiri MCP-Native ETL Pipeline
Discover how etl-pipeline-mcp processes high-velocity webhooks, executes automated PII scrubbing, performs cross-platform identity resolution, and streams clean data into enterprise warehouses.
6. Database & Cloud Infrastructure Bridge (`seosiri-db-infra-mcp`)
Gives AI agents safe, read-only access to production databases and audit visibility into cloud infrastructure, without ever exposing write or mutation paths.
- Secure Live Database Querying: Executes parameterized, SELECT-only Postgres queries — no writes, no mutations.
- Schema Inspection: Extracts table schemas, column data types, and indexes on demand.
- AWS S3 Security Audits: Inspects bucket policies, encryption settings, and public-access block flags.
- Cloudflare Infrastructure Control: Audits Worker deployment states and routes.
- Dynamic PII/PHI Masking: Applies column-level masking to query result sets before they ever reach the agent.
Verified tools: execute_readonly_postgres_query, inspect_database_schema_tree, audit_aws_s3_bucket_security, check_cloudflare_worker_deployment_status, mask_sensitive_query_columns, enforce_query_timeout_guardrails, export_query_parquet_buffer, sanitize_database_input_payload, get_live_db_throughput_metrics, get_db_server_specifications (10 tools).
SEOSiri Database Infrastructure Guide: Secure Query, Schema & Cloud Audit Architecture
Explore the complete guide on seosiri-db-infra-mcp — read-only Postgres querying, live schema inspection, AWS S3 bucket security audits, and Cloudflare Worker deployment control.
Group 3 · Bioscience & Clinical
7. High-Throughput Screening & Clinical Bridge (`seosiri-bioassay-mcp`)
Bridges AI agents with HTS assay mathematics, medical device telemetry, and clinical data standards.
- Multi-Assay Support: TR-FRET, UA-Glo, ELISA, and HICA assay calculations.
- Multi-Tier Biological Modeling: Sub-Cellular, Cellular, Tissue, and Organism segments.
- Medical Device Telemetry: Ingests and processes device output streams.
- HL7 FHIR v4.0.1 Conversion: Converts clinical observations into the FHIR standard for interoperability with hospital and CRO systems.
Sovereign Bio-Assays & HTS Automation: The BioAssay MCP Architecture
Explore the complete technical blueprint on seosiri-bioassay-mcp — bridging AI agents with TR-FRET, UA-Glo, ELISA, and HICA assays across Sub-Cellular, Cellular, Tissue, and Organism tiers, with native HL7 FHIR v4.0.1 observation conversions.
Group 4 · AI-Native SEO, AEO & GEO Governance
This group of five servers exists because the underlying discipline itself has shifted. For the strategic case behind that shift, see our cornerstone paper on Traditional SEO vs. Modern Wave AEO/GEO, which frames why entity-based, answer-engine-native optimization now sits alongside classic keyword ranking rather than replacing it outright.
8. AI Visibility Auditor (`seosiri-aeo-geo-mcp`)
- /llm.txt Compliance Auditing for AI-crawler discoverability.
- RFC 9116 security.txt Verification for vulnerability disclosure headers — if you haven't deployed one yet, see Deploying RFC Security.txt via Cloudflare Workers at the Edge.
- AEO Answer-Card Extraction formatted for Perplexity, SearchGPT, and Google AI Overviews.
- Content Stickiness Analytics for retention measurement.
Verified tools: audit_llm_txt_compliance, audit_security_txt_compliance, calculate_geo_ai_readiness_score, analyze_content_stickiness, extract_aeo_answer_cards, fetch_tranco_authority_rank, validate_schema_markup_density, sanitize_geo_payload, get_live_aeo_throughput_metrics, get_aeo_server_specifications (10 tools).
Sovereign AEO & GEO Intelligence: The AEO/GEO MCP Architecture
Explore the complete blueprint on seosiri-aeo-geo-mcp — auditing /llm.txt compliance, verifying RFC 9116 security.txt headers, and extracting AEO answer cards.
9. Semantic Keyword Intelligence (`seosiri-keyword-cluster-mcp`)
Automates semantic keyword clustering, intent classification, and topical authority mapping using local-first vector techniques.
Verified tools: cluster_keywords_by_similarity, classify_search_intent, detect_keyword_cannibalization, generate_topical_authority_map, calculate_keyword_difficulty_score, extract_lsi_semantic_variants.
Semantic Keyword Intelligence: The Keyword Cluster MCP Architecture
Explore the complete guide on seosiri-keyword-cluster-mcp — automating semantic keyword clustering, search intent classification, cannibalization audits, and local-first vector retrieval.
10. Automated Schema Engineering (`seosiri-content-schema-mcp`)
- Multi-Entity Schema.org JSON-LD graph compilation.
- GA4 API Metric Guardrail Validation.
- /llm.txt Compliance Auditing.
- Content Retention/Stickiness Analytics.
Verified tools: generate_tech_article_schema, generate_faq_page_schema, validate_ga4_report_metrics, calculate_content_stickiness_score, validate_llm_txt_formatting, audit_rfc_9116_security_txt, extract_structured_answer_snippets, sanitize_content_payload, get_live_schema_throughput_metrics, get_schema_server_specifications (10 tools).
Automated Schema Engineering & GA4 Data Sync Architecture
Explore the complete guide on seosiri-content-schema-mcp — compiling multi-entity Schema.org JSON-LD graphs, validating GA4 API metric guardrails, and auditing /llm.txt compliance.
11. DNS & TLS Security Auditor (`seosiri-dns-sec-audit-mcp`)
- DNS Record Auditing.
- SOA Expire Health Checks.
- SSL/TLS Certificate Inspection.
- HTTP Response Security Header Analysis — for the measured ranking impact of getting this right, see our Security Headers & GEO Ranking Case Study.
Verified tools: audit_dns_records, check_soa_expiry_health, audit_http_security_headers, check_ssl_tls_certificate, validate_well_known_security_txt, validate_well_known_llm_txt, calculate_technical_seo_security_score, sanitize_audit_payload, get_live_dns_throughput_metrics, get_dns_server_specifications (10 tools).
Technical SEO & Security Auditing: The DNS SEC Audit MCP Architecture
Explore the complete guide on seosiri-dns-sec-audit-mcp — automating DNS record audits, SOA Expire health checks, SSL/TLS certificate inspection, and HTTP response security header analysis.
12. AI Search Governance & Crawl Control (`seosiri-search-governance-mcp`)
- robots.txt Enforcement for GPTBot, ClaudeBot, and other AI crawlers.
- Canonical Link Integrity Verification.
- Brand Safety Guardrails.
- Real-Time IndexNow Dispatch.
Verified tools: audit_ai_crawler_directives, verify_canonical_link_integrity, enforce_brand_safety_guardrails, audit_xml_sitemap_index, notify_indexnow_search_engines, check_http_redirect_chain, validate_google_bot_user_agent, sanitize_governance_payload, get_live_governance_throughput_metrics, get_governance_server_specifications (10 tools).
Autonomous AI Search Governance: The Search Governance MCP Architecture
Explore the complete guide on seosiri-search-governance-mcp — enforcing robots.txt rules for GPTBot & ClaudeBot, verifying canonical link integrity, and dispatching real-time IndexNow notifications.
13. Knowledge Graph Engine (`seosiri-semantic-entity-mcp`)
Establishes a local-first control plane for entity resolution, transforming unstructured brand content into structured, verifiable facts that AI search systems can ground answers in.
- Named Entity Extraction for persons, organizations, products, and technologies.
- Wikidata QID Disambiguation resolving entity names to canonical Wikidata and Wikipedia URLs.
- sameAs Schema Linking compiling structured Schema.org JSON-LD arrays.
- Knowledge Graph Triple Construction generating RDF-style Subject-Predicate-Object triples, exportable as Parquet buffers for DuckDB or S3.
Verified tools: extract_named_entities, disambiguate_wikidata_entity, generate_sameas_schema_links, calculate_entity_salience_score, construct_knowledge_graph_triples, audit_entity_density_ratio, export_graph_parquet_buffer, sanitize_entity_payload, get_live_entity_throughput_metrics, get_entity_server_specifications (10 tools).
Knowledge Graph Engineering: The SEOSiri Semantic Entity MCP Server Architecture
Explore the complete guide on seosiri-semantic-entity-mcp — automating named entity extraction, Wikidata QID disambiguation, sameAs schema linking, and Knowledge Graph triple construction.
Group 5 · Enterprise Operations & Incident Response
14. Incident Response Bridge (`seosiri-ops-comm-mcp`)
Connects AI agents to the operational tools engineering teams already use for triage, tracking, and communication during incidents.
- Sentry Error Triage: Parses raw exception payloads and stacktraces, and correlates timestamps against GitHub commit history to surface likely culprits.
- Algorithmic Severity Scoring: Computes an incident severity score (0–100).
- Linear Issue Sync: Compiles structured issue payloads with priority tags.
- Slack Incident Dispatch: Formats and sends Slack Block Kit alerts to operational channels.
- Blameless Postmortems: Generates postmortem reports in Markdown.
Verified tools: parse_sentry_error_stacktrace, format_linear_issue_payload, dispatch_slack_incident_alert, correlate_github_commit_culprit, calculate_incident_severity_score, generate_incident_postmortem_markdown, export_ops_parquet_buffer, sanitize_ops_payload, get_live_ops_throughput_metrics, get_ops_server_specifications (10 tools).
SEOSiri Operations & Incident Response: The Ops Comm MCP Architecture
Explore the complete guide on seosiri-ops-comm-mcp — automating Sentry error triage, Linear issue sync, and Slack incident response for engineering teams.
Sovereign Biopharma Software Infrastructure: The Biopharma MCP Architecture
Explore our complete technical architecture on @seosiri/biopharma-mcp — connecting AI agents with 4PL sigmoidal dose-response curve fitting, CDISC SDTM v1.7 exports, FDA 21 CFR Part 11 audit trails, and zero-latency HIPAA PII redaction.
Group 6 · AI-Driven Pedagogy
15. Pedagogical Brain (`learning-orchestrator-mcp`)
Replaces un-structured AI tutoring with deterministic educational standards:
- Bloom's Taxonomy Assessment Generator: Generates evaluation questions mapped to cognitive dimensions.
- SuperMemo SM-2 Spaced Repetition Engine: Calculates optimal review dates from recall grades (0–5) and ease factors, using timezone-aware UTC objects.
- LMS LTI/SCORM Sync Bridge: Maps SCORM quiz scores to SM-2 quality grades and outputs signed LTI Outcomes payloads.
Verified tools: get_progressive_syllabus, generate_skills_assessment, calculate_spaced_repetition, sync_ai_platform_state, sync_lms_onboarding_state.
16. VS Code Extension & Model Context Protocol Suite Manager (vscode.seosiri.com)
The seosiri-vscode-mcp-manager serves as the central developer orchestrator across Visual Studio Code, Cursor AI, and Claude Desktop, while providing native OpenAI Responses API Remote MCP Tool Connector generation.
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 display 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
Method 1: The Unified Gateway (Recommended — Single Endpoint)
Connect to all 15 SEOSiri MCP servers through our Cloudflare Zero Trust Edge Gateway at mcp.seosiri.com. Add this block to your claude_desktop_config.json:
{
"mcpServers": {
"seosiri-unified-gateway": {
"command": "uv",
"args": [ "run", "mcp-remote", "https://mcp.seosiri.com" ]
}
}
}
Method 2: Standalone Servers via GitHub (Zero-Setup)
All fifteen servers have a public GitHub repository — connect directly with uv — no cloning required:
{
"mcpServers": {
"seosiri-biorobotics": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/biorobotics", "src/main_mcp_server.py"]
},
"seosiri-api-guard": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/seosiri-api-guard-mcp-server", "src/main_server.py"]
},
"seosiri-data-pipeline": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/lambda-data-pipeline-mcp", "src/main_server.py"]
},
"seosiri-etl-pipeline": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/etl-pipeline-mcp", "src/main_server.py"]
},
"seosiri-db-infra": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/seosiri-db-infra-mcp", "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"]
},
"seosiri-keyword-cluster": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/keyword-cluster-mcp", "src/main_server.py"]
},
"seosiri-bioassay": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/bioassay-mcp", "src/main_server.py"]
},
"seosiri-aeo-geo": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/aeo-geo-mcp", "src/main_server.py"]
},
"seosiri-content-schema": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/content-schema-mcp", "src/main_server.py"]
},
"seosiri-dns-sec-audit": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/dns-sec-audit-mcp", "src/main_server.py"]
},
"seosiri-search-governance": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/search-governance-mcp", "src/main_server.py"]
},
"seosiri-semantic-entity": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/semantic-entity-mcp", "src/main_server.py"]
},
"seosiri-ops-comm": {
"command": "uv",
"args": ["run", "--github", "SEOSiri-Official/ops-comm-mcp", "src/main_server.py"]
}
}
}
Method 3: PyPI-Published Servers (pip / uvx Install)
Most servers are also published to PyPI as an alternative to the GitHub method above:
pip install etl-pipeline-mcp --break-system-packages pip install seosiri-bioassay-mcp --break-system-packages pip install seosiri-aeo-geo-mcp --break-system-packages pip install seosiri-dns-sec-audit-mcp --break-system-packages pip install seosiri-content-schema-mcp --break-system-packages pip install seosiri-search-governance-mcp --break-system-packages pip install seosiri-keyword-cluster-mcp --break-system-packages pip install seosiri-semantic-entity-mcp --break-system-packages # Or run directly without installing uvx etl-pipeline-mcp
Method 4: Direct API / cURL Queries (Directory Introspection)
To programmatically query metadata for the GitHub-hosted servers via Glama's directory API:
curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/biorobotics' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/seosiri-api-guard-mcp-server' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/lambda-data-pipeline-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/etl-pipeline-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/seosiri-db-infra-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/learning-orchestrator-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/biometric-iot-bridge-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/keyword-cluster-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/bioassay-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/aeo-geo-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/content-schema-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/dns-sec-audit-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/search-governance-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/semantic-entity-mcp' curl -X GET 'https://glama.ai/api/mcp/v1/servers/SEOSiri-Official/ops-comm-mcp'
Queries
Question: What is the SEOSiri Model Context Protocol (MCP) Ecosystem?
Answer: The SEOSiri MCP Ecosystem is an open-source suite of fifteen specialized Model Context Protocol servers engineered by Momenul Ahmad. It covers bio-robotic kinematics, multi-industry API security, bioassay science, big data ingestion, knowledge graph engineering, AI-native SEO/AEO/GEO governance, enterprise operations and incident response, mobile biometric IoT authentication, and AI-driven pedagogy.
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. 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: What does the SEOSiri Bioassay MCP server do?
Answer: seosiri-bioassay-mcp bridges AI agents with High-Throughput Screening assay mathematics — TR-FRET, UA-Glo, ELISA, and HICA — across Sub-Cellular, Cellular, Tissue, and Organism biological tiers, and converts clinical observations to the HL7 FHIR v4.0.1 standard.
Question: What does the SEOSiri AEO/GEO MCP server audit for AI search visibility?
Answer: seosiri-aeo-geo-mcp audits /llm.txt compliance, verifies RFC 9116 security.txt headers, and extracts AEO answer cards formatted for Perplexity, SearchGPT, and Google AI Overviews.
Question: How does the Search Governance MCP server manage AI crawler access?
Answer: seosiri-search-governance-mcp enforces robots.txt rules for AI crawlers such as GPTBot and ClaudeBot, verifies canonical link integrity, applies brand safety guardrails, and dispatches real-time IndexNow notifications.
Question: How does the SEOSiri data pipeline execute Identity Stitching and GDPR compliance simultaneously?
Answer: The pipeline ingests high-velocity webhooks into an in-memory Hot Tier and schedules batch CRM polls to an on-disk Cold Tier. 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: What does the SEOSiri Database & Cloud Infrastructure MCP server do?
Answer: seosiri-db-infra-mcp gives AI agents read-only, parameterized access to production Postgres databases with SELECT-only validation, live schema inspection, dynamic column-level PII/PHI masking, AWS S3 bucket security auditing, and Cloudflare Worker deployment status checks — with no write or mutation paths exposed.
Question: Can I deploy SEOSiri's MCP servers on Windows, macOS, or Linux?
Answer: Yes. All fifteen servers are built using cross-platform Python and have public GitHub repositories reachable via uv run --github. Most are also published to PyPI for standard pip or uvx installation. All are compatible with Windows, macOS, and Linux, over stdio transport or inside lightweight Docker containers.
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.
📚 Related Architecture Guides
Every server and strategy referenced above has its own deep-dive on the blog. This hub post indexes the full set:
Search, AEO & GEO
- Sovereign AEO & GEO Intelligence: The SEOSiri AEO-GEO MCP Server Architecture
- Traditional SEO vs. Modern Wave AEO/GEO: Strategic Paradigm Shift
- Automated Schema Engineering & GA4 Data Sync: The SEOSiri Content Schema MCP Architecture
- Technical SEO & Security Auditing: The SEOSiri DNS SEC Audit MCP Server Architecture
- Semantic Keyword Intelligence & RAG Retrieval: The SEOSiri Keyword Cluster MCP Architecture
- AI Search Governance & Indexing Interlocks: The SEOSiri Search Governance MCP Architecture
- Knowledge Graph Engineering: The SEOSiri Semantic Entity MCP Server Architecture
Enterprise Operations & Incident Response
Big Data, Security & Enterprise Pipelines
- Sovereign Data Engineering: The SEOSiri MCP-Native ETL Pipeline Architecture
- SEOSiri Database Infrastructure Guide: Secure Query, Schema & Cloud Audit Architecture
- Security Headers & GEO Ranking Case Study: Edge Infrastructure Deployment
- Deploying RFC Security.txt via Cloudflare Workers at the Edge
Life Sciences, Bio-Robotics & Physical IoT
- Sovereign Bio-Assays & HTS Automation: The SEOSiri BioAssay MCP Server Architecture
- SEOSiri Bio-Robotics Core Engine: AI-Driven Lab Automation & Kinematics
- The Biometric IoT Bridge Technical Architecture: Decoupling AI and Physical Hardware
💼 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 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, custom PHI/PII masking rules) inside secure, on-premise container networks.
- Enterprise Big Data & Warehouse Exports: Customizing high-velocity webhook ingestion streams and identity stitching feeds directly into corporate Snowflake, ClickHouse, or BigQuery instances.
- AI-Native SEO Infrastructure: Deploying custom search-governance, schema, and DNS-security auditing pipelines tuned to enterprise brand safety policy.
- Mobile Biometric Hardware Relays: Connecting our open-source biometric_iot_bridge Flutter Package directly to 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:
Enterprise Support Email: [email protected]
⚠️ Safety & Regulatory Note
All bionics, robotics, clinical-data, 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.
