JevGuard MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| TYPESAFE_API_KEY | No | API key for TypeSafe AI. Required for dispatching upstream when the cache misses; optional if only using local deterministic evaluation. |
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
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| jevguard_evaluateA | Executes the deterministic JevGuard evaluation pipeline including state pruning, closed-world escape injection, certainty calibration, and 0-token caching. |
| jevguard_calibrateA | Evaluates probability distributions across answers to identify ambiguity, low confidence (top_prob < 0.40), and flat distributions (dispersion_gap < 0.15). |
| jevguard_prune_stateA | Sanitizes and prunes complex JSON state payloads by removing nulls, empty collections, collapsing whitespace, and protecting against cyclic references. |
| jevguard_cache_fingerprintB | Calculates a canonical SHA-256 fingerprint from state and questions with volatile key masking (timestamp, trace_id, request_id) for 0-token deterministic caching. |
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 4 tools
Each tool has a clearly distinct purpose: calibration assesses probability distributions, evaluate runs the full pipeline, prune_state sanitizes JSON, and cache_fingerprint computes hashes. No overlap or ambiguity between them.
All tools follow a consistent 'jevguard_' prefix with verb_noun naming (calibrate, evaluate, prune_state, cache_fingerprint). The pattern is uniform and predictable.
Four tools is well within the ideal range for a focused server. Each tool serves a specific step in the JevGuard workflow without unnecessary bloat.
The tools cover the core pipeline stages (calibration, evaluation, state pruning, caching) but might benefit from a dedicated tool for retrieving or reporting results. Minor gap, but the set is largely complete for its stated purpose.