Prototipo · Versión preliminar: todos los servidores del registro oficial, sincronizados cada 30 minutos. Las reseñas y las cuentas llegarán en una etapa posterior.
PopNx MCPServidores MCP para quienes usan IA · explicados con palabras sencillas

Kosha Model Discovery

de sriinnuversión 1.13.0i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.sriinnu/kosha-discovery

Instalar

Resumen

Descripción del creador (original en inglés)

Tells your agent which model to use and what it costs, across 46 providers and local runtimes.

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en tu computadora
  • Transporte: stdio
  • Categoría: Otros
  • Debes completar: ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, OPENROUTER_API_KEY, XAI_API_KEY, TYPESAFE_API_KEY

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

  • Revisiones básicas: 1 de 1 superadas
  • Se ejecuta en tu computadora con los permisos de tu usuario (archivos, red, apps).
  • Debes completar tú: ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, OPENROUTER_API_KEY, XAI_API_KEY, TYPESAFE_API_KEY, KOSHA_CACHE_TTL_HOURS

Los valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.

Necesitas

  • npmNode.js instalado (para el comando npx)

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json

{
  "mcpServers": {
    "kosha-discovery": {
      "command": "npx",
      "args": [
        "-y",
        "@sriinnu/kosha-discovery"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "OPENAI_API_KEY": "your-value",
        "GOOGLE_API_KEY": "your-value",
        "OPENROUTER_API_KEY": "your-value",
        "XAI_API_KEY": "your-value",
        "TYPESAFE_API_KEY": "your-value",
        "KOSHA_CACHE_TTL_HOURS": "your-value"
      }
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add kosha-discovery --env ANTHROPIC_API_KEY=your-value --env OPENAI_API_KEY=your-value --env GOOGLE_API_KEY=your-value --env OPENROUTER_API_KEY=your-value --env XAI_API_KEY=your-value --env TYPESAFE_API_KEY=your-value --env KOSHA_CACHE_TTL_HOURS=your-value -- npx -y @sriinnu/kosha-discovery

Completa los valores vacíos antes de ejecutarlo.

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

{
  "mcpServers": {
    "kosha-discovery": {
      "command": "npx",
      "args": [
        "-y",
        "@sriinnu/kosha-discovery"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "OPENAI_API_KEY": "your-value",
        "GOOGLE_API_KEY": "your-value",
        "OPENROUTER_API_KEY": "your-value",
        "XAI_API_KEY": "your-value",
        "TYPESAFE_API_KEY": "your-value",
        "KOSHA_CACHE_TTL_HOURS": "your-value"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

{
  "servers": {
    "kosha-discovery": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@sriinnu/kosha-discovery"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "OPENAI_API_KEY": "your-value",
        "GOOGLE_API_KEY": "your-value",
        "OPENROUTER_API_KEY": "your-value",
        "XAI_API_KEY": "your-value",
        "TYPESAFE_API_KEY": "your-value",
        "KOSHA_CACHE_TTL_HOURS": "your-value"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Valores que debes completar

  • ANTHROPIC_API_KEY secreto env
    Anthropic API key. Optional — without it, Anthropic models are read from the public models.dev / LiteLLM catalogs instead of the live API.
  • OPENAI_API_KEY secreto env
    OpenAI API key. Optional — falls back to the public catalogs when absent.
  • GOOGLE_API_KEY secreto env
    Google AI Studio / Gemini API key. Optional.
  • OPENROUTER_API_KEY secreto env
    OpenRouter key. Optional for discovery (unauthenticated requests are rate-limited), required to execute through OpenRouter.
  • XAI_API_KEY secreto env
    xAI (Grok) API key. Optional.
  • TYPESAFE_API_KEY secreto env
    TypeSafe System One (Jev) API key. Optional.
  • KOSHA_CACHE_TTL_HOURS env
    Override the discovery cache TTL. Defaults to 24 hours.

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 8 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub sriinnu, dueña del repo

  • … Aún sin revisar

    Sigue en mantenimiento

    Todavía no hemos leído este repo en GitHub

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • – No aplica

    El endpoint responde

    Este se ejecuta en tu computadora; no hay endpoint en internet

  • – No aplica

    Inicio de sesión con OAuth

    Se ejecuta en tu computadora y usa ajustes locales en su lugar

  • … Aún sin revisar

    Sin instrucciones ocultas en las descripciones de herramientas

    Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Otrosi

  • Más estrellas que el 0% de los otros 18431 servidores de esta categoría
  • Publicado en el registro más recientemente que el 92% de los otros 18431 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 18431 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro Kosha Model Discovery?

Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

Debes completar: ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, OPENROUTER_API_KEY, XAI_API_KEY, TYPESAFE_API_KEY

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (1.13.0) llegó al registro hace 3 días.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Spec Driven Development, Remote Desktop Commander, Tethered Trust

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

Spec Driven Development

de formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Se ejecuta en tu computadora★ 440MITActualizado hace 14 meses
Instalar

Remote Desktop Commander

de desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Se ejecuta en la nube★ 211Actualizado hace 3 días
Instalar

Tethered Trust

de tetheredtrust.com

Fit, compatibility and recall checks for AI agents before they buy: verdicts, evidence, receipts.

Se ejecuta en la nubeActualizado hoy
Instalar

README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

kosha-discovery

Tells your agent — or your code — which model to use and what it costs.

Website: kosha.srinivas.dev

kosha discovers models across 46 providers and local runtimes, finds your API keys wherever they already live (env vars, Claude CLI, Codex, gcloud ADC, AWS SSO), fills in pricing and context limits, and answers questions like *the cheapest model with tool use and 128k context that I actually hold a key for*. It ships as a TypeScript library, a CLI, an HTTP API, an OpenAI-compatible proxy with a spend ledger, and an MCP server.

It works with no API keys at all — discovery falls back to the public models.dev and LiteLLM catalogs, so kosha list is useful on a fresh machine.

Install

npm install @sriinnu/kosha-discovery       # library / server

npm install -g @sriinnu/kosha-discovery # global kosha CLI brew install sriinnu/tap/kosha # same CLI and MCP server, via Homebrew

Requires Node.js 22+.

Quick start

Library
import { createKosha } from "@sriinnu/kosha-discovery";

const kosha = await createKosha();

const models = kosha.models(); // ModelCard[] across every provider const cheapest = kosha.cheapestModels({ role: "image" }); // ranked by price, with missingCredentials const sonnet = kosha.model("sonnet"); // alias → canonical ID; undefined if unknown console.log(sonnet?.pricing); // { inputPerMillion: 2, outputPerMillion: 10, cacheReadPerMillion: 0.2, ... }

CLI
kosha discover                       # query every provider; writes ~/.kosha/cache and the manifest

kosha list --provider anthropic # read from the local cache kosha model sonnet # one model, alias-aware kosha routes claude-opus-5-5 # every serving route for a model (direct, OpenRouter, Bedrock, …) kosha cheapest --role embeddings # rank by price for a role kosha doctor --ci --model opus,gpt6 # fail CI if a model you pin is deprecated, retiring, or gone kosha spend --since 2026-09-01 # roll up the proxy's spend ledger kosha refresh # bypass the cache and re-discover kosha serve --port 3000 # HTTP API + proxy; binds 127.0.0.1 (see Proxy below)

Every command takes --json. kosha --help lists the rest.

After each discovery, a stable v1 manifest lands at ~/.kosha/registry.json:

jq '.models[] | select(.pricing.inputPerMillion < 0.1) | .modelId' ~/.kosha/registry.json
GitHub Action

Fail a build when a model your code pins is deprecated, about to be retired, or listed by no provider any more:

- uses: sriinnu/kosha-discovery@v1

with: models: | claude-opus-5-5 gpt-6-sol sonnet

Pin it to a commit SHA rather than a moving tag, as you would any action. The action runs the kosha version it was released with, not latest, so a new npm publish does not change what your CI runs until you move the pin.

It runs kosha doctor --ci --model … against the public catalogs (no provider keys needed), writes a table to the job summary, and annotates each failing model. A reseller retiring one of its routes is reported but does not fail the build while the model's own provider still serves it; deprecation-window (default 30 days) sets how far ahead a sunset counts.

Public snapshot

A weekly discovery run publishes a full snapshot — every provider, model, price and limit kosha can see without your keys — at a stable URL:

curl -sL https://github.com/sriinnu/kosha-discovery/releases/download/snapshot-latest/kosha-latest.json \

| jq '.modelCount, .providerCount'

It is a release asset rather than a file in the repository: at ~2.8 MB growing with every provider added, committing it weekly would put roughly 150 MB of already-stale data a year into a repo people are meant to clone. Dated snapshot-YYYY-MM-DD pre-releases keep a short trail for diffing, pruned to the two most recent, and an older one is only removed once a newer one exists.

Each snapshot's release notes list what changed since the previous one — new models, repricings, new deprecations, removals. The same diff runs locally with pnpm snapshot:diff old.json new.json.

HTTP API
GET  /api/models?provider=&originProvider=&mode=&capability=

GET /api/models/:idOrAlias GET /api/models/:idOrAlias/routes GET /api/models/cheapest?role=… GET /api/capabilities GET /api/providers[/:id] GET /api/roles GET /api/resolve/:alias GET /api/discovery-errors GET /api/discovery[/delta|/watch|/cheapest|/binding] (stable v1 contract) POST /api/refresh GET /health GET /metrics GET /proxy/v1/models POST /proxy/v1/chat/completions

Parameters and response shapes: docs/api.md.

Proxy

kosha serve also exposes an OpenAI-compatible endpoint at /proxy/v1. Point any OpenAI SDK at it; the proxy resolves the model or alias, picks a provider you hold credentials for, injects the upstream key, forwards the request, and writes a row to the spend ledger.

kosha serve   # start on :3000
import OpenAI from "openai";

const client = new OpenAI({ baseURL: "http://localhost:3000/proxy/v1", apiKey: "not-used", // kosha resolves credentials from env });

// Use any canonical model ID or alias const res = await client.chat.completions.create({ model: "sonnet", messages: [{ role: "user", content: "hello" }], });

// Let kosha pick the cheapest model you have a key for const cheap = await client.chat.completions.create({ model: "kosha:cheapest", messages: [{ role: "user", content: "hello" }], });

// Cheapest model with tool_use and at least 128k context const routed = await client.chat.completions.create({ model: "kosha:cheapest[tool_use,128k]", messages: [{ role: "user", content: "hello" }], });

`kosha:cheapest` filter syntax (comma-separated, combinable):

FilterExampleMeaning
capabilitytool_use, visionmodel must have this tag
k128k, 200kminimum context window
provider: provider:groqpin to a specific provider

kosha:fastest, kosha:reliable, and kosha:balanced take the same filters and rank on observed latency and circuit-breaker state instead of price.

Every response carries x-kosha-model, x-kosha-provider, x-kosha-requested, x-kosha-attempt-chain, and x-kosha-estimated-cost-usd; non-streaming responses add x-kosha-actual-cost-usd when the upstream returned a usage block.

What the proxy can forward:

Upstream wire formatProvidersSupport
OpenAI-compatibleOpenAI, Ollama, OpenRouter, Vercel, Groq, Together, Fireworks, DeepInfra, …passthrough, streaming included
Anthropic MessagesAnthropictranslated: streaming, tools, image_url, response_format, reasoning_effort; audio input and non-function tools fail over to an OpenAI-compatible route for the same model
Cloud SDKsGoogle, Bedrock, Vertexdiscovery only, not proxied yet
Non-chat / other wireTypeSafe, Thinking Machinesdiscovery only — TypeSafe's System One endpoint is not a chat API, and Tinker's Anthropic-wire path differs from Anthropic's own

Defaults that matter before you expose it: the server binds 127.0.0.1. Pass --host 0.0.0.0 (or KOSHA_HOST) to listen on a network interface, and set KOSHA_PROXY_TOKEN so /proxy/* and POST /api/refresh require Authorization: Bearer or x-kosha-token. KOSHA_MONTHLY_BUDGET_USD caps spend per calendar month. Reference: docs/api.md, docs/operations.md.

MCP server

kosha-mcp serves the registry over the Model Context Protocol on stdio, so an agent can call kosha_query_models, kosha_cheapest_model, kosha_ranked_routes, kosha_model_detail, kosha_model_routes, kosha_resolve_alias, kosha_provider_health, and kosha_context_strategy without an HTTP server.

claude mcp add kosha -- kosha-mcp

It is published to the MCP registry as io.github.sriinnu/kosha-discovery, so clients that read the registry can install it without a manual command. The manifest is server.json.

Every provider key is optional. With no credentials at all the server still answers from the public models.dev and LiteLLM catalogs plus a curated offline list, so it is useful on a fresh machine.

Tools and protocol details: docs/mcp.md.

Supported providers

46 providers. Each has a descriptor in src/provider-catalog.ts; most OpenAI-compatible ones are driven from GENERIC_OPENAI_PROVIDERS in src/discovery/generic-openai.ts rather than a hand-written class.

ProviderDiscoveryCredential sources
AnthropicGET /v1/models (context, output cap, capabilities read from the API)ANTHROPIC_API_KEY, Claude CLI, Codex CLI
OpenAIGET /v1/modelsOPENAI_API_KEY
GoogleGET /v1beta/modelsGOOGLE_API_KEY, GEMINI_API_KEY, Gemini CLI, gcloud
AWS BedrockSDK → CLI → public catalog → static listAWS_ACCESS_KEY_ID, ~/.aws/credentials, SSO, IAM
Vertex AIAPI → gcloud → public catalog → static listGOOGLE_APPLICATION_CREDENTIALS, ADC
Ollama, llama.cpp, LM Studio, vLLMlocal HTTP APInone
OpenRouterAPIOPENROUTER_API_KEY (optional; unauthenticated is rate-limited)
Vercel AI GatewayGET /v1/modelsAI_GATEWAY_API_KEY, VERCEL_OIDC_TOKEN (discovery works without; execution needs one)
NVIDIA, Together, Fireworks, Groq, Cerebras, Cohere, DeepInfra, PerplexityOpenAI-compatible API _API_KEY
DeepSeek, Mistral, Moonshot (Kimi), GLM (Zhipu), Z.AI, MiniMaxOpenAI-compatible API _API_KEY
xAI (Grok)GET /v1/models; Grok Imagine split into image / videoXAI_API_KEY
TypeSafe (System One / Jev)GET /v1/models — returns judgment models, not chatTYPESAFE_API_KEY, JEV_API_KEY
Thinking Machines (Inkling)Anthropic-wire endpoint, no model list — public catalog onlyTINKER_API_KEY
Alibaba Model Studio (Qwen), Volcengine Ark (Doubao), Inception (Mercury), AI21 (Jamba), Upstage (Solar), StepFun, Meta (Muse Spark)OpenAI-compatible APIDASHSCOPE_API_KEY, ARK_API_KEY, INCEPTION_API_KEY, AI21_API_KEY, UPSTAGE_API_KEY, STEPFUN_API_KEY, META_MODEL_API_KEY
Baseten, Nebius Token Factory, Novita AI, SiliconFlow, Hugging Face, Ollama CloudOpenAI-compatible API _API_KEY, HF_TOKEN
Regional pairs

Several providers run separate hosts for international and mainland-China traffic, with separate keys and separate price sheets — Qwen 2.5 72B is $1.40/M input internationally against $0.574/M in China. Merging them would make a model's price depend on which host answered last, so each region is its own provider:

InternationalChinaDiffers in
moonshot (api.moonshot.ai)moonshot-cn (api.moonshot.cn)host, key
minimax (api.minimax.io)minimax-cn (api.minimaxi.com)host, key
alibaba (dashscope-intl)alibaba-cn (dashscope)host, key, pricing
siliconflow (.com)siliconflow-cn (.cn)host, key, pricing

| stepfun (api.stepfun.ai) | stepfun-cn (api.stepfun.com) | host, key, prici

Solo se muestra el principio; lee el resto en el repo

Pregunta a PopNx