Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Tells your agent which model to use and what it costs, across 46 providers and local runtimes.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, OPENROUTER_API_KEY, XAI_API_KEY, TYPESAFE_API_KEY, KOSHA_CACHE_TTL_HOURSLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿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-discoveryCompleta los valores vacíos antes de ejecutarlo.
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.
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.
KOSHA_CACHE_TTL_HOURS envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 8 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub sriinnu, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
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.
Debes completar: ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, OPENROUTER_API_KEY, XAI_API_KEY, TYPESAFE_API_KEY
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).
El repo de GitHub cambió por última vez –, y la última versión (1.13.0) llegó al registro hace 3 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Tethered Trust
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Fit, compatibility and recall checks for AI agents before they buy: verdicts, evidence, receipts.
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.
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.
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+.
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, ... }
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
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.
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.
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.
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):
| Filter | Example | Meaning |
|---|---|---|
| capability | tool_use, vision | model must have this tag |
k | 128k, 200k | minimum context window |
provider: | provider:groq | pin 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 format | Providers | Support |
|---|---|---|
| OpenAI-compatible | OpenAI, Ollama, OpenRouter, Vercel, Groq, Together, Fireworks, DeepInfra, … | passthrough, streaming included |
| Anthropic Messages | Anthropic | translated: 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 SDKs | Google, Bedrock, Vertex | discovery only, not proxied yet |
| Non-chat / other wire | TypeSafe, Thinking Machines | discovery 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.
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.
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.
| Provider | Discovery | Credential sources |
|---|---|---|
| Anthropic | GET /v1/models (context, output cap, capabilities read from the API) | ANTHROPIC_API_KEY, Claude CLI, Codex CLI |
| OpenAI | GET /v1/models | OPENAI_API_KEY |
GET /v1beta/models | GOOGLE_API_KEY, GEMINI_API_KEY, Gemini CLI, gcloud | |
| AWS Bedrock | SDK → CLI → public catalog → static list | AWS_ACCESS_KEY_ID, ~/.aws/credentials, SSO, IAM |
| Vertex AI | API → gcloud → public catalog → static list | GOOGLE_APPLICATION_CREDENTIALS, ADC |
| Ollama, llama.cpp, LM Studio, vLLM | local HTTP API | none |
| OpenRouter | API | OPENROUTER_API_KEY (optional; unauthenticated is rate-limited) |
| Vercel AI Gateway | GET /v1/models | AI_GATEWAY_API_KEY, VERCEL_OIDC_TOKEN (discovery works without; execution needs one) |
| NVIDIA, Together, Fireworks, Groq, Cerebras, Cohere, DeepInfra, Perplexity | OpenAI-compatible API | _API_KEY |
| DeepSeek, Mistral, Moonshot (Kimi), GLM (Zhipu), Z.AI, MiniMax | OpenAI-compatible API | _API_KEY |
| xAI (Grok) | GET /v1/models; Grok Imagine split into image / video | XAI_API_KEY |
| TypeSafe (System One / Jev) | GET /v1/models — returns judgment models, not chat | TYPESAFE_API_KEY, JEV_API_KEY |
| Thinking Machines (Inkling) | Anthropic-wire endpoint, no model list — public catalog only | TINKER_API_KEY |
| Alibaba Model Studio (Qwen), Volcengine Ark (Doubao), Inception (Mercury), AI21 (Jamba), Upstage (Solar), StepFun, Meta (Muse Spark) | OpenAI-compatible API | DASHSCOPE_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 Cloud | OpenAI-compatible API | _API_KEY, HF_TOKEN |
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:
| International | China | Differs 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