jev-screen-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| JEV_MODEL | No | Model id sent to the endpoint | jev-latest |
| JEV_BASE_URL | No | API base URL | https://api.typesafe.ai/v1/systemone |
| JEV_MCP_MOCK | No | Set to '1' to force the deterministic offline mock | 0 |
| TYPESAFE_API_KEY | No | TypeSafe Jev key. Absent ⇒ mock mode | |
| JEV_MCP_TIMEOUT_MS | No | Per-call timeout (ms) | 30000 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| screen_contentA | Content-moderation & classification gate powered by Jev (System One decision model). Given text, returns spam and toxicity probabilities, a category, a severity score, a calibrated confidence, and an action (allow / review / block). Low confidence routes to review; clear, severe violations route to block. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion between tools. The single tool has a clear, unique purpose.
The lone tool name 'screen_content' follows a consistent verb_noun pattern. Since there is only one tool, naming is trivially consistent.
A single tool is borderline for a server named 'jev-screen-mcp'. It could be well-scoped for a narrow text-screen function, but typically a moderation server would offer more operations (e.g., different content types).
The tool covers text classification and decision-making, but lacks other content modalities (image, video, URL) and batch processing. This is a notable gap for a general 'screen' service, though it may be intentionally limited to text.