A sovereign, high-speed, local-first Big Data Ingestion, Filtering, and Analytical Pipeline Orchestrator over the Model Context Protocol.
Server has 4 tools with basic schemas and descriptions, but significant quality gaps. All tools have descriptions (10-200 chars, within baseline range) and input schemas with typed parameters. However, naming lacks clarity (ingest_realtime_webhook vs ingest_batch_api_poll are similar; process_lambda_pipeline is vague). No output schemas documented. Error handling is minimal, responses are JSON strings without structured error guidance. Parameters lack enums for constrained values (e.g., target_warehouse should be enum, not free string). No tool annotations (readOnlyHint/destructiveHint). Security concern: WEBHOOK_SECRET_KEY hardcoded in source. Missing pagination for export_to_data_warehouse. Per-tool average: 42/100.
Simulates exporting the anonymized, prioritized, and stitched historical dataset from the Cold Storage DB directly to an enterprise data warehouse (Snowflake/ClickHouse/BigQuery).
Ingests heavy, non-real-time data (CRM profiles) directly to on-disk Cold Storage. Executes PII redaction and maps unique stitched identities instantly.
Ingests high-velocity, real-time events (CMS, email opens, social mentions) directly into the Hot Tier. Verifies webhook authenticity via HMAC-SHA256.
Migrates Hot Tier events to Cold Storage, executing ID stitching, PII anonymization, and priority scoring.
No output schemas documented. LLMs cannot infer what fields to expect from tool responses, forcing unstructured parsing and downstream lookup calls.
Hardcoded webhook secret (WEBHOOK_SECRET_KEY = b'seosiri_secure_webhook_handshake_2026') in source code. Credentials must use server-side secret injection via environment variables.
Vague tool name 'process_lambda_pipeline' does not start with clear action verb. Does it migrate, transform, filter, or aggregate? Ambiguous names cause LLM selection errors.
target_warehouse parameter accepts free-form string instead of enum. Should constrain to [SNOWFLAKE, CLICKHOUSE, BIGQUERY] to prevent hallucinated values.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 56 | 2026-07-28+ | v2 |
Error responses are JSON strings without structured error classification. LLMs cannot determine if errors are retryable, user-fixable, or fatal.