TuringCorp
A decision model for the calls that don't have a right answer. The better option, with a reason.
¿Debería usar esto?
Calidad y seguridad
Hallazgos (2)
- HIGH
- MEDIUMen decide
Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.
Costo de contexto
Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.
Instalar
Instalación con un clic
Agrega esto a tu archivo `claude_desktop_config.json`:
{
"mcpServers": {
"decider": {
"url": "https://mcp.turingcorp.net/mcp"
}
}
}Puntos de conexión remotos
https://mcp.turingcorp.net/mcpstreamable-httpQué puede hacer
Inventario de herramientas
Herramientas (2)
🟢decide(task, optionA, optionB)
Use this when you must choose between two concrete options and both are defensible - two plans, two drafts, two diagnoses, two vendors - and you have no objective way to pick. Not for: more than two options; anything an objective rule settles (a spec, a test, a price, a document); factual lookup; paths that must answer in seconds; high-stakes irreversible calls without review. Fill it in: state task neutrally, without leaning toward either side; give one concrete plan per option - never bundle alternatives into a single one ("go indoors or postpone"); keep the two sides comparable in length. Returns the decision inline: betterOption ("option_A" or "option_B"), confidence (e.g. "76.7%"), reason and job_id, all in the same tool result. There is nothing to poll and nothing to fetch afterwards. Reserve 180-300 seconds: this is a long call, and the timeout is a client/host setting, not a parameter you pass. If the call is cut off, do NOT call again - a retry is a new paid call. Retrieve it instead with the get_result tool (same job_id): read-only, free, and no credential of your own needed; with no job_id it lists the ids for your credential. A host that declares the io.modelcontextprotocol/tasks extension can use tasks/get instead. The confidence is the point: it is calibrated, not decorative. On both published benchmarks accuracy rises with it - JudgeBench 99.6% in the 90%+ band down to 67.7% below 70%; the harder ContextualJudgeBench 83.3% down to 55.4% - so route on it: act on a high value, review or escalate a low one, instead of trusting a bare pick. Tables, sample sizes and method: https://api.turingcorp.net Judged by an independent panel, not by a model grading its own output. Read it as a reference, not an instruction, a result, or a prediction; set your own threshold, and apply your own review policy for high-stakes or irreversible decisions. Auth: Agent Pass as `Authorization: Bearer <pass>` (issued at https://agent-pass.turingcorp.net, valid 7 days; each decision is a paid call). On invalid_credential, sign in there and re-roll. Errors: a credential problem is rejected before the call - HTTP 401 with WWW-Authenticate; a business failure (e.g. insufficient balance) comes back as a tool result with isError true plus a second JSON block {error, http_status, action_url, message}, where http_status is the upstream status (the tool call itself is HTTP 200).
Esquema de entrada
{
"type": "object",
"properties": {
"task": {
"type": "string",
"description": "The decision to make, stated neutrally and without a preferred answer."
},
"optionA": {
"type": "string",
"description": "First candidate and the case for it."
},
"optionB": {
"type": "string",
"description": "Second candidate and the case for it."
}
},
"required": [
"task",
"optionA",
"optionB"
],
"$schema": "https://json-schema.org/draft/2020-12/schema"
}Esquema de salida
{
"type": "object",
"properties": {
"job_id": {
"description": "Identifier of this decision, also usable to retrieve the stored result for 7 days with the get_result tool. Keep it: if the call times out, retrieve the result with get_result instead of calling again, which would be a new paid call.",
"type": "string"
},
"betterOption": {
"type": "string",
"enum": [
"option_A",
"option_B"
],
"description": "Which option was preferred, using the same values as the REST API."
},
"confidence": {
"type": "string",
"pattern": "^\\d{1,3}\\.\\d%$",
"description": "This service's own judgement of how far apart the two options were, as a percentage (e.g. \"76.7%\"). A reference for your own decision-making - not an instruction, not a result. Observed accuracy by range is published at https://api.turingcorp.net"
},
"reason": {
"type": "string",
"description": "Why the chosen option was preferred."
}
},
"required": [
"betterOption",
"confidence",
"reason"
],
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false
}🟢get_result(job_id)
Use this to retrieve the result of an earlier TuringCorp tool call by its job_id - for example a call that was cut off by a client timeout, or one whose id you were given. Retrieval is read-only and free: it starts no new work and costs nothing, so it is always safe to retry. With job_id: that call's status, and once it has finished the same payload the call would have returned inline. Without job_id: the ids available to your credential (7 days). If a call was cut off, retrieve it here instead of calling again - a retry is a new paid call. A job that is not yours and a job that does not exist are answered identically, on purpose. If your client declares the io.modelcontextprotocol/tasks extension, tasks/get reaches the same job.
Esquema de entrada
{
"type": "object",
"properties": {
"job_id": {
"description": "Identifier returned by an earlier TuringCorp call (also usable at GET /v1/jobs?job_id=<id>). Omit it to list the ids available to your credential.",
"type": "string"
}
},
"$schema": "https://json-schema.org/draft/2020-12/schema"
}Comunidad
Evidencia