jev-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| JEV_MCP_MODEL | No | Selects the model to use; defaults to 'jev-latest'. | jev-latest |
| TYPESAFE_API_KEY | Yes | API key for TypeSafe, required by the server. | |
| JEV_MCP_MAX_STATE_CHARS | No | Compatibility alias for JEV_MCP_MAX_REQUEST_CHARS, accepted for one release. | |
| JEV_MCP_MATCH_DEADLINE_S | No | Deadline in seconds for jev_match; defaults to 45. | 45 |
| JEV_MCP_MAX_REQUEST_CHARS | No | Maximum serialized request budget in characters for state and questions sent to the service; defaults to 120,000. | 120000 |
| JEV_MCP_MATCH_MAX_CANDIDATES | No | Maximum number of candidates for jev_match; defaults to 2,000. | 2000 |
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": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| jev_askB | Use Jev for typed judgments over supplied state; it is not for text generation or numeric extraction. Confidence is distribution concentration, not correctness. The default est_cost_usd uses the published early-access input price and may change. |
| jev_classifyA | Use Jev to select one label from a closed list; it is not for text generation or numeric extraction. Confidence is distribution concentration, not correctness. With order-ensemble enabled, order flips concentrate at low confidence, so disagreement is a second, cheap reason to route to a person. The default est_cost_usd uses the published early-access input price and may change. |
| jev_scoreB | Use Jev to place state on an ordered situation rubric; it is not for text generation or numeric extraction. Confidence is distribution concentration, not correctness. The default est_cost_usd uses the published early-access input price and may change. |
| jev_checkB | Use Jev for independent yes/no checks over state; it is not for text generation or numeric extraction. Confidence is distribution concentration; Noul probability is evidence strength. The default est_cost_usd uses the published early-access input price and may change. |
| jev_matchA | Find the best candidate with an explicit abstention signal; it is not text generation. Candidates are evaluated in windows, and |
| jev_screenB | Use Jev to screen untrusted text; it is a filter, not a security boundary. Confidence is distribution concentration, not correctness. The default est_cost_usd uses the published early-access input price and may change. |
| jev_healthA | Use Jev health to inspect the configured model and the account's available models and release dates. Health checks report zero estimated cost; the published early-access input price may change for other tools. |
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 7 tools
Each tool maps to a distinct judgment mode: open typed judgment, closed-list classification, ordered scoring, yes/no checking, candidate matching, text screening, and health inspection. The generic jev_ask could broadly overlap with the more specific modes, but the descriptions clarify when each should be used.
All tools share the consistent jev_ prefix and use short lowercase names matching their action or purpose. The naming convention is uniform and predictable across the entire set.
Seven tools is a well-scoped set for a single Jev judgment API. Each tool covers a distinct operation without redundancy, and the count feels neither thin nor bloated.
The tool surface covers the core judgment types Jev appears to support: ask, classify, score, check, match, and screen, plus health for configuration introspection. The repeated exclusions of text generation and numeric extraction indicate those are intentionally out of scope rather than missing.