Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Tells your agent which model to use and what it costs, across 46 providers and local runtimes.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, OPENROUTER_API_KEY, XAI_API_KEY, TYPESAFE_API_KEY, KOSHA_CACHE_TTL_HOURSAls geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"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"
}
}
}
}Führe das in deinem Terminal aus
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-discoveryTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"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"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"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"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
KOSHA_CACHE_TTL_HOURS envDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto sriinnu bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Das musst du eintragen: ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, OPENROUTER_API_KEY, XAI_API_KEY, TYPESAFE_API_KEY
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.13.0) kam vor 3 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, 好縮 Short
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Smart URL shortener: create, tag and track short links on s.gooo.name.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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
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