Model Context Protocol server for Datashift trust infrastructure. Enables AI agents to submit tasks for human review, manage review queues, and track task completion through real-time notifications.
Three tools with complete schemas and descriptions, but quality varies. submit_task has good parameter detail (queue_key, data, context, metadata, summary with maxLength constraint). list_queues and get_queue_config are minimal, descriptions are adequate but lack actionable context for LLM selection. No output schemas documented. Parameter descriptions are present but generic (e.g., 'The queue key/identifier' lacks format/constraint guidance). No error handling guidance visible. Tool names follow verb_noun pattern correctly. Missing: pagination guidance for list_queues, idempotency hints for submit_task, and recovery instructions for failures.
Get detailed configuration for a specific queue. Returns review type, result options, assignment strategy, and SLA settings.
List all queues available to the organization. Returns queue configurations including review types and assignment strategies.
Submit a task for human review to a queue. Automatically subscribes to completion notifications. Returns the task details and resource URI for tracking.
Output schemas not documented. LLMs cannot infer what fields list_queues and get_queue_config return, forcing guesswork on downstream tool calls.
list_queues lacks pagination parameters (limit, offset, cursor) and total count in response. Large queue lists will blow context window.
No error handling guidance. Descriptions do not explain what happens on invalid queue_key, permission denial, or API failure, or how LLM should recover.
submit_task description lacks idempotency guarantee. LLMs retry on ambiguous failures, tool must clarify if re-submitting same task creates duplicate or returns existing.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | C | 63 | <=2025-11-25 | v2 |
Parameter descriptions are generic. 'The queue key/identifier' does not specify format (alphanumeric, slug, UUID), length, or case sensitivity. LLMs cannot validate input.