jev-mcp

An MCP server that exposes TypeSafe Jev as typed judgment tools.

Jev is a System One model. It returns a typed answer and a calibrated probability distribution, never prose. These tools surface that faithfully rather than hiding it behind a label.

Install

Requires Node 20.12+ and a TypeSafe API key from console.typesafe.ai.

Claude Code plugin

One marketplace add, one install. This registers the server and the agent skill together, so there is no separate skill step.

/plugin marketplace add rashedInt32/jev-mcp
/plugin install jev@jev-mcp

The plugin runs the published package through npx -y jev-mcp@<version>, so nothing needs building. The first launch downloads the package, so allow a few seconds before the server shows as connected in claude mcp list.

Any MCP client

claude mcp add --scope user jev -- npx -y jev-mcp

Or in a client's JSON config:

{
  "mcpServers": {
    "jev": { "command": "npx", "args": ["-y", "jev-mcp"] }
  }
}

Do not register the server directly and install the plugin. Two servers named jev will otherwise both register.

The key

The server reads the key from TYPESAFE_API_KEY in its environment, then from JEV_API_KEY, then from ~/.config/typesafe/key. It is never a tool argument, so it cannot land in a transcript or in a model's context.

The key file is the most reliable source, because some MCP clients strip the environment before spawning servers:

mkdir -p ~/.config/typesafe
printf '%s' "ts_..." > ~/.config/typesafe/key
chmod 600 ~/.config/typesafe/key

If you prefer the variable, put it in ~/.zshenv rather than in any repo, and make sure it is exported. Without export the variable exists only in the shell that read it, and every server Claude Code spawns fails with a missing-key error.

Plugin internals

The server is declared inline under mcpServers in .claude-plugin/plugin.json. There is no .mcp.json anywhere in the repo, and that is deliberate.

A .mcp.json at the plugin root is auto-discovered by the plugin loader, so it works. But any session opened in this directory also reads that same file as a project config, where ${CLAUDE_PLUGIN_ROOT} is undefined. The result is a missing-variable warning and a scope conflict on the same server name. The inline form has exactly one loader and produces neither. Verify with claude mcp list: the server appears as plugin:jev:jev and the diagnostics section stays empty.

One trap. claude plugin details jev reports MCP servers (0) for an inline declaration even while the server is connected and working. That is a gap in the inventory count, not a failure. Trust claude mcp list over plugin details here.

The plugin deliberately ships no env block. Naming the key there would expand to an empty string when the variable is unset, and an empty string is not nullish, so it would shadow the ~/.config/typesafe/key fallback and turn a working setup into a missing-key error. Leaving env out keeps all three key sources live.

Tools

Tool	Primitive	Use when
jev_classify	Choice	The answer is one of a fixed set you define
jev_score	Score	The answer is a degree on an ordered scale
jev_check	Noul	The answer is yes or no, and you want the probability
jev_ask	all three	You have several questions about the same state
jev_models	—	Confirm the key works and find a model id

Every tool returns the full probability distribution alongside the answer, plus confidence for Choice and Score. Results come back as MCP structured content, so a client gets typed data rather than a JSON string to re-parse.

Prefer jev_ask

Jev prefills the state once and scores every question in a single forward pass, so extra questions add almost no latency or cost. TypeSafe's own measurement on a document-dominated workload puts one batched call at 12.2x cheaper and 10.0x faster than one call per question, with no change in the answers.

Questions in one request cannot see each other's answers. State any speculative premise explicitly and let your own code decide which answers apply.

Design rules

1. The caller owns the option set. jev_classify requires options from you, so

the model can pick the wrong one but can never invent one. A selector cannot choose a candidate the enumerator dropped. This is the single most common way these integrations fail.

1. Probabilities are always returned. Not just the winner.
2. The key lives in the environment. Never in an argument.
3. Nothing is silently dropped, overwritten, or truncated. A request that cannot

be honoured exactly fails with a reason instead of quietly changing meaning.

1. Only JSON-RPC reaches stdout. Logs go to stderr, always.
2. Every answer is checked against the question sent. A choice that was never

offered, a distribution over the wrong options, a legend that does not match the levels, or a missing answer in a batch is an error of kind malformed_response, never a result. A caller that trusted the label alone would otherwise execute something it never proposed.

The no-match option

Each selecting tool adds a none option by default so the model can decline rather than being forced to pick. Turn it off with add_none: false when one option must always apply.

If you already use the name none for an option of your own, the added option takes a different key instead of overwriting yours, and the response reports which key carries the no-match meaning in none_option. Your option and its probability always survive intact.

Confidence gating

Choice and Score answers include an action of act, review, or abstain, derived from confidence and the thresholds you pass in act_above and review_above (defaults 0.8 and 0.5). jev_check returns a verdict of yes, no, or uncertain from yes_at_or_above and no_at_or_below (defaults 0.7 and 0.3).

These defaults are starting points, not universal rules. Calibrate them on your own data and on what it costs to be wrong; a destructive action deserves a higher bar than a read-only one. Confidence describes how concentrated the distribution is. It is not a claim that the answer is correct.

A Noul near 0.5 means yes and no are close to equally likely, not that the answer is "medium", which is why the middle band reports uncertain rather than rounding.

Errors

Failures come back with isError and a classified body: kind, retryable, and where available status, requestId, and a hint. A rejected key (authentication, never retryable) is distinguishable from a rate limit (rate_limit, retryable) and from a malformed question (invalid_request) and from an answer that fails validation against the question (malformed_response, retryable, nothing to act on). The SDK already retries 408, 429, and 5xx with backoff before an error surfaces here.

Every judgment result also carries latency_ms for the API round trip, so calibration notes can record cost alongside confidence.

Limits

A Choice question accepts at most 255 options, which is an API limit; past that, search in two passes, one question picking a window and a second ranking within it. Question count and state size are local caps that bound cost on a single call, and both are configurable. Oversized state is rejected rather than truncated, because truncating silently changes the material the judgment rests on.

Agent skill

skills/jev/SKILL.md teaches an agent when to reach for these tools and how to shape the call. It is a bridge, not a tutorial. Primitive semantics, state design, and composition patterns live in TypeSafe's own typesafe-ai skill and in the docs, so this one deliberately does not repeat them.

Its first section is a three-way test: answer it yourself, call a tool, or write SDK code. That test follows the same line as When not to reach for this below, so an agent loading the skill does not end up arguing with this README.

Point your client at the directory, or copy the file to ~/.claude/skills/jev/.

Configuration

Variable	Effect
TYPESAFE_API_KEY	Required. JEV_API_KEY also works.
JEV_MODEL	Model id. Defaults to jev-latest.
JEV_TIMEOUT_MS	Per-attempt timeout. Defaults to 15000.
JEV_MAX_QUESTIONS	Questions per jev_ask. Defaults to 64.
JEV_MAX_STATE_CHARS	Largest state accepted. Defaults to 200000.
TYPESAFE_LOG_LEVEL	SDK verbosity. Safe at any level; all output goes to stderr.

An unusable value for any numeric setting falls back to the default and warns on stderr, rather than becoming NaN and disabling the limit it was meant to enforce.

Troubleshooting

Every call reports a missing key. Some MCP clients filter the environment before spawning servers, which drops TYPESAFE_API_KEY. Confirm the variable is exported, then pass it explicitly in the client's server config if it still does not arrive. Run jev_models to check the key in isolation.

The server connects and then dies. On a stdio transport, anything written to stdout that is not JSON-RPC breaks the connection. This server routes all logging to stderr, so TYPESAFE_LOG_LEVEL=debug is safe to turn on while debugging.

When not to reach for this

Jev earns its place on a decision that repeats thousands of times inside software, where code can enumerate the options first and you need a number to threshold on.

For a one-off judgment during a conversation, an ordinary model answer is usually better, because it comes with reasoning you can argue with. Jev gives you a number and a label. That is a feature at scale and a limitation in dialogue.

If deterministic code already decides the case correctly, keep the deterministic code. Typed output guarantees the interface, not the truth. Measure before adopting.

Do not ask Jev to compute. It is a one-pass chooser with no scratchpad, so counting, arithmetic, date comparison, and threshold cutoffs are unreliable, and the answer still comes back with a confident probability. Do that work in code and pass the result in as a fact. Add a reference date to state for any question about "today". See TypeSafe's numeric and date limitations.

Development

npm ci
npm run build
npm run typecheck
npm test          # offline: unit tests plus regression tests against a local stand-in
npm run test:e2e  # live, requires TYPESAFE_API_KEY

Inside this repo the plugin's server fails to connect. npx jev-mcp@<version> sees a local project already named jev-mcp at that version, skips the registry, and looks for a bin that is never linked into the project's own node_modules. Every other directory is fine. For work in this checkout, register the local build directly and skip the plugin, since the plugin always launches the published version:

claude mcp add --scope user jev -- node /absolute/path/to/jev-mcp/dist/index.js

Releasing: bump version in package.json, .claude-plugin/plugin.json, and .claude-plugin/marketplace.json together, then npm publish. The plugin cache is keyed by version, so an unbumped plugin keeps serving the old snapshot.

The offline suite runs the real built server over stdio against a local stand-in for the TypeSafe API and asserts on the request bodies it actually sends, so a regression in what reaches the model fails the build.

License

MIT