Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Prompt evals over MCP: run a prompt on your dataset, score each output 1-5 with an LLM judge.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
Authorization비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.
터미널에서 이 명령어를 실행하세요
claude mcp add --transport http evals https://completionkit.com/mcp --header 'Authorization: your-value'실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"evals": {
"url": "https://completionkit.com/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"evals": {
"type": "http",
"url": "https://completionkit.com/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
Authorization 비밀 필수 HTTP header이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
아직 이 서버의 도구 목록을 읽지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 도메인 completionkit.com 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
입력해야 할 값: Authorization
제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.0.0)은 4개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Your prompts need tests too.
Run every prompt against real data. Score each output with an LLM judge against criteria you define. Change anything: the prompt, the model, the temperature, the dataset. Re-run and see exactly what got better and what broke. When the scores tell you something's off, CompletionKit suggests an improved prompt based on the judge's actual feedback on your runs. You inspect the diff, apply it as a new version, and verify the improvement.
It's the difference between "this prompt seems to work" and "this prompt scores 4.3 out of 5 across 200 inputs, up from 3.8 last version."
[Start on completionkit.com →](https://completionkit.com) | [RubyGems](https://rubygems.org/gems/completion-kit)
Just want to use it? CompletionKit Cloud is the same engine, fully hosted — zero install, no Rails ops, plans at completionkit.com/pricing.
Same engine, same UI, same REST API and MCP server — pick the deployment that fits. The first two are stack-agnostic: you run CompletionKit as a product and talk to it over HTTP and MCP, whatever language your own app is written in. The third is for teams already building on Rails.
The fastest path. Sign up and you're running on the same engine you'd self-host, without touching a Rails app. No db:migrate, no Puma, no Solid Queue, no provider key management — multi-tenant workspaces, your team logs in, you go. Plans at completionkit.com/pricing.
Run it on your own infra as a self-contained product. There's nothing to integrate and no Ruby to write — once it's up, you drive everything through the web UI, the REST API, and the MCP server, from whatever stack your own app is built in. It needs Postgres and a host that can run the app (Fly, Render, Heroku, Docker, …).
git clone https://github.com/homemade-software-inc/completion-kit.git
cd completion-kit/standalone bundle install bin/rails completion_kit:install:migrations bin/rails db:migrate
Run both a web server and a Solid Queue worker. In two terminals:
bin/rails server
bin/jobs
Or with foreman in one terminal: foreman start -f Procfile.dev.
Visit http://localhost:3000. Add a provider credential (Settings), create a prompt, upload a CSV dataset, and run it. See Deploying self-hosted for the production-env setup.
gem "completion-kit"
bin/rails generate completion_kit:install
bin/rails db:migrate
The engine mounts at /completion_kit. Generate / judge flows enqueue Active Job jobs (CompletionKit::GenerateRowJob, CompletionKit::JudgeReviewJob, CompletionKit::RunCompletionCheckJob), so your host app needs an Active Job adapter that actually processes them — Solid Queue, Sidekiq, GoodJob, etc. The :async adapter is not suitable for production: it runs jobs in the web Puma's thread pool with no durability and no retry, and a long LLM call will block request handling.
Host-app layout integration. If your host app overrides the engine layout (e.g. layout "application" on engine controllers, or rendering engine views inside your own shell), include both the engine's stylesheet and JavaScript in that layout:
<%= stylesheet_link_tag "completion_kit/application", media: "all" %>
<%= javascript_include_tag "completion_kit/application", defer: true, nonce: true %>
Without the JavaScript include, in-page behaviours silently fail: clickable table rows, dialogs, copy buttons, the API token reveal, the run form, live run status, live tag-breadcrumb updates, relative-time ticking, CSV row hover-expand, model-refresh progress, focus-first-error, and local-time formatting.
Content Security Policy. The engine's pages have no inline event handlers or inline scripts, and the engine layout puts the request nonce on its script tags, so the pages work under a nonce-based script-src. The views still use inline style attributes, so leave style-src out of the nonce directives and allow 'unsafe-inline' there for now.
Use a nonce that lasts the whole session, not a fresh random one per request. Turbo Drive re-creates the scripts in each new page body with the nonce from the csp-nonce meta tag, but the browser keeps enforcing the policy header of the first page it loaded, so a per-request nonce blocks nonce scripts after the first Drive visit.
Keep a random nonce in the session, and skip it for API controllers so cookie-less API and MCP calls get no session cookie, as the example below does. The Rails default, ->(request) { request.session.id.to_s }, also lasts the session, but it is empty on a brand-new visitor's first response, so a policy that admits scripts only by nonce blocks that first page's scripts until the session exists.
Rails.application.configure do
config.content_security_policy do |policy| policy.default_src :self policy.script_src :self policy.style_src :self, :unsafe_inline end
config.content_security_policy_nonce_generator = lambda do |request| next if request.controller_instance.is_a?(ActionController::API)
request.session[:csp_nonce] ||= SecureRandom.base64(16) end config.content_security_policy_nonce_directives = %w(script-src) end
CompletionKit discovers available models from each provider's API automatically.
| Provider | Env vars | What it covers |
|---|---|---|
| OpenAI | OPENAI_API_KEY | GPT-5, GPT-4.1, GPT-4o, etc. |
| Anthropic | ANTHROPIC_API_KEY | Claude Opus, Sonnet, Haiku |
| Ollama / local endpoint | OLLAMA_API_ENDPOINT (default: http://localhost:11434/v1), OLLAMA_API_KEY (optional) | Any model you've ollama pull-ed, or any OpenAI-compatible local server (vLLM, LM Studio, llama.cpp) |
| OpenRouter | OPENROUTER_API_KEY | 100+ models from 30+ providers through one API key |
| Azure AI Foundry | No env var — add via the Providers UI / a ProviderCredential (api_key + api_endpoint required, api_version optional) | Azure OpenAI deployments and Foundry projects |
Set these as environment variables or configure them in the generated initializer. You can also add provider credentials through the web UI under Settings.
The Ollama key from OLLAMA_API_KEY or config.ollama_api_key goes only to the Ollama endpoint from OLLAMA_API_ENDPOINT or config.ollama_api_endpoint, or to http://localhost:11434/v1 when neither is set and config.allow_loopback_endpoints is on, which is the default. A provider credential with no key of its own gets that key only while it points at that same endpoint. Point it anywhere else and CompletionKit sends no key, so store the key on the credential itself. A key stored on a credential always goes to that credential's endpoint. Two endpoints match when their scheme, host, port and path match. The case of the scheme and host, a default port written out, a trailing slash and a trailing /v1 make no difference. A blank stored key counts as no key.
Provider API keys are encrypted at rest using Active Record encryption. You need three encryption keys configured before the app will boot in production.
Generate them:
bin/rails db:encryption:init
Then set them as environment variables:
COMPLETION_KIT_ENCRYPTION_PRIMARY_KEY=<generated value>
COMPLETION_KIT_ENCRYPTION_DETERMINISTIC_KEY= COMPLETION_KIT_ENCRYPTION_KEY_DERIVATION_SALT=
Or add them to config/credentials.yml.enc under active_record_encryption. In development, the standalone app uses built-in fallback values so you can skip this step locally.
CompletionKit requires authentication in any deployed environment. In development and test, routes are open by default (with a log warning); every other environment returns 403 until auth is configured.
CompletionKit.configure do |c|
c.username = "admin" c.password = ENV["COMPLETION_KIT_PASSWORD"] end
CompletionKit.configure do |c|
c.auth_strategy = ->(controller) { controller.authenticate_user! } end
Only one mode can be active.
When someone records a verdict on a judge's score in the web UI, CompletionKit saves it under a reviewer name. Each reviewer keeps one verdict per response and metric, so give every person their own name. Otherwise their verdicts overwrite each other. Set current_reviewer to a callable that receives the controller and returns the signed-in person's name:
CompletionKit.configure do |c|
c.auth_strategy = ->(controller) { controller.authenticate_user! } c.current_reviewer = ->(controller) { controller.current_user&.email } end
The callable must return a String or nil. Any other value, such as a user record, raises CompletionKit::ConfigurationError. If current_reviewer is unset or returns a blank value, verdicts are saved under username, or "operator" when no username is set. The web UI does not read the X-Remote-User header on its own. If a proxy in front of your app sets that header, pass it through:
CompletionKit.configure do |c|
c.current_reviewer = ->(controller) { controller.request.headers["X-Remote-User"] } end
Only use this header when a trusted proxy always overwrites it. Otherwise any client can send it and claim any reviewer name.
The REST API and the MCP server take the reviewer name from their own created_by parameter.
The REST API, the MCP endpoint, and the web UI are rate limited per IP, per minute. The defaults are generous; tune them in the initializer:
CompletionKit.configure do |c|
c.api_rate_limit = 120 # REST API + MCP, requests per minute (default 120) c.web_rate_limit = 300 # web UI, requests per minute (default 300) end
Limiting uses Rails.cache. A shared cache store (Solid Cache, Redis) throttles accurately across multiple app instances; a per-process store still throttles each instance independently.
Uploads, prompt templates, and regex check patterns have limits, so one large or hostile input cannot tie up a worker. Tune them in the initializer:
CompletionKit.configure do |c|
c.max_upload_bytes = 25 * 1024 * 1024 # largest dataset CSV or import file (default 25 MB) c.max_template_bytes = 1024 * 1024 # largest prompt template (default 1 MB) c.regex_timeout = 1.0 # seconds a regex check may spend matching one row (default 1.0) end
A prompt whose template is over max_template_bytes fails validation when its template is saved. Prompts saved before a
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요