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제작자가 쓴 설명(영어 원문)
Verified tool calls for Claude Code: verify, retry and fallback over hermetic claude calls.
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.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"conductor": {
"command": "npx",
"args": [
"-y",
"@fainir/conductor"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add conductor -- npx -y @fainir/conductor프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"conductor": {
"command": "npx",
"args": [
"-y",
"@fainir/conductor"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"conductor": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@fainir/conductor"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 10일 점검
레지스트리 이름이 GitHub 계정 fainir 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
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.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.4.1)은 11일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: GitHub, Desktop Commander, Cloudflare MCP
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:↓ 주간 다운로드i★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Verified tool calls for Claude Code: an MCP server (installable as a plugin) whose 23 tools check their own output in code before you get it.
A model asked to "extract the email" or "redact the phone numbers" is usually right, and nothing tells you when it isn't. conductor puts each job behind a contract: an input schema, an output schema and a mandatory verifier. Deterministic jobs (slugs, base64, URL extraction) run as plain code and never touch a model. Judgment jobs (summaries, PII redaction) run as hermetic claude -p calls, and an answer that fails its verifier is retried with the failure as feedback, handed to a fallback, or returned as a failure; it is never silently passed through.
The skeleton (validate -> execute -> verify -> retry -> fallback -> log) is real code that cannot be skipped; the model is quarantined to the judgment-shaped holes.
You need Claude Code installed and logged in, and Node.js 20 or newer on your PATH (the plugin starts the server with node).
claude plugin marketplace add fainir/conductor
claude plugin install conductor@conductor
Restart Claude Code (or run /reload-plugins in a running session). Inside a session the same steps are /plugin marketplace add fainir/conductor and /plugin install conductor@conductor. Check that the server is up:
$ claude mcp list
plugin:conductor:conductor: node /Users/you/.claude/plugins/cache/conductor/conductor/0.4.1/dist/conductor-mcp.cjs - ✓ Connected
Then ask for the job in plain words, for example "redact the PII in this ticket with conductor". The tools show up as mcp__plugin_conductor_conductor__ .
Update with claude plugin marketplace update conductor && claude plugin update conductor@conductor, remove with claude plugin uninstall conductor@conductor.
Without the plugin system. dist/conductor-mcp.cjs is a committed, self-contained bundle, so a clone needs no install or build step:
git clone https://github.com/fainir/conductor
claude mcp add conductor -s user -- node "$PWD/conductor/dist/conductor-mcp.cjs"
Other MCP clients can run npx -y @fainir/conductor, which serves MCP over stdio. The unrelated conductor-mcp package on npm belongs to someone else.
Every tool returns the same envelope. Real output from the bundle for base64_encode with {"text": "hello"}:
{ "ok": true, "output": { "encoded": "aGVsbG8=" }, "via": "base64_encode", "attempts": 1, "verdict": { "ok": true, "score": 1 } }
via names the rung that produced the answer (the tool itself, a declared fallback, or freeform for plain Claude), and attempts counts tries on that rung. A failure sets ok: false and the tool result's isError, and the verdict says why, so the calling model can fix its call:
{ "ok": false, "via": "redact_pii", "attempts": 0,
"verdict": { "ok": false, "score": 0, "feedback": "invalid input: input: missing required property 'text'; input: unexpected property 'txt' (allowed: text)" } }
From a clone you can drive the same loop with the CLI (npm ci first). Pure tools answer instantly and cost nothing:
$ npx tsx src/cli.ts slugify '{"text":"Hello, World!"}'
{ "ok": true, "output": { "slug": "hello-world" }, "command": "slugify", "attempts": 1, "verdict": { "ok": true, "score": 1 }, "costUsd": 0 }
$ npx tsx src/cli.ts normalize_phone '{"phone":"call me"}' { "ok": false, "command": "normalize_phone", "attempts": 1, "verdict": { "ok": false, "score": 0, "feedback": "shape: normalized must match /^\\+?\\d{6,15}$/ (an optional leading '+' followed by 6-15 digits)" }, "costUsd": 0 }
The CLI exits 1 when the result fails verification. Model-backed tools work the same way (npx tsx src/cli.ts extract_contact '{"text":"Call Sam at sam@acme.io"}') and spend a claude -p call per attempt. npx tsx src/cli.ts with no arguments lists the commands, and npx tsx src/cli.ts route "make a url slug" '{"text":"Hello World"}' lets a model pick the command.
| tool | input | what it does | verifier checks |
|---|---|---|---|
slugify | text | Convert a string into a URL-safe slug. | non-empty; only [a-z0-9] runs joined by single hyphens |
word_count | text | Count the words and characters in a string. Words are whitespace-separated tokens of the trimmed text; chars is the raw length of the input. | recomputes both counts |
normalize_phone | phone | Normalize a phone string to canonical '[+]digits' form by stripping non-digit characters. | recomputes; optional + then 6-15 digits |
truncate | text, max | Truncate text to at most max characters, appending a single-character ellipsis when it must be cut. | length never exceeds max; recomputes |
dedupe_lines | text | Split text on newlines and keep the first occurrence of each line, preserving order. | no duplicates; every line comes from the input; recomputes |
extract_urls | text | Extract all http(s) URLs from a text, deduped while preserving first-seen order. | http(s) shape; each URL appears in the input |
template_fill | template, data | Fill a template by replacing every {{key}} token with String(data[key]); fails, naming the keys, if any {{key}} has no value in data. | recomputes; no {{placeholder}} left |
base64_encode | text | Encode a UTF-8 string to base64. | decodes back to the input |
base64_decode | encoded | Decode a base64 string to UTF-8 text. | re-encodes to the input (padding and line breaks ignored) |
extract_emails | text | Extract all email addresses from text. | email shape; each address appears in the input |
json_minify | json | Minify a JSON string by removing insignificant whitespace. | parses to the same value as the input |
to_snake_case | text | Convert a string to snake_case. | recomputes |
claude -p call)| tool | input | what it does | verifier checks |
|---|---|---|---|
extract_contact | text | Extract a contact's name, email, and phone from a blob of text. | schema; email and phone shape; the email must appear in the input (grounding) |
summarize | text, max_sentences? | Summarize a blob of text in at most a few sentences, using only the text itself. | at most max_sentences (default 2); not longer than the input |
extract_keywords | text, k? | Extract up to k salient keywords or short phrases that appear verbatim in the input text. | 1 to k items (default 5); each appears verbatim in the input |
classify_sentiment | text | Classify the overall sentiment of a piece of text as positive, negative, or neutral. | label is one of the three; confidence in 0..1 |
redact_pii | text | Replace every email address and phone number in the input text with [REDACTED], leaving all other text unchanged. | no email or phone pattern left; [REDACTED] present when the input had PII |
json_extract | text, fields | Extract a caller-specified list of fields from a blob of text into a JSON object. Each requested field becomes a key; the value is null when the field is absent from the text. | data is an object with every requested field as a key |
fix_json | text | Repair malformed or loosely-formatted JSON text into a valid JSON value. | json is an object or array |
extract_dates | text | Extract every date referenced in a piece of text, normalized to ISO format YYYY-MM-DD. | each is a real calendar date in YYYY-MM-DD |
categorize | text, categories | Choose the single best-fitting category for a piece of text from a provided list of categories. | exactly one of the given categories |
translate | text, target_language | Translate a piece of text into a given target language. | non-empty; at most 5x the input length + 20 |
detect_language | text | Detect the natural language of text. | non-empty name; two-letter lowercase ISO 639-1 code |
Inputs ending in ? are optional. The first three columns come from the command manifests (npm test fails if they drift); the full JSON Schemas are what the MCP server advertises.
input -> inputSchema check -> run the command -> verify -> ok? -> result
^ | no +-- retry with the verifier's feedback (model-backed, up to maxAttempts) | still no declared fallbacks -> freeform (plain Claude, same schema, same verifier)
commands/ /index.ts: a manifest (input and output JSON Schema, determinism, prompts, fallbacks) plus a verify() export. A command without a verifier cannot be registered (src/library.ts, src/registry.ts). Mechanical checks come first (schema, regex, recompute, grounding); llmJudge in src/verify.ts exists for criteria no code can express.inputSchema is rejected before anything runs, with a message that names the problem.pure commands are deterministic code: run once, cached, free, and never sent to a model. stochastic commands are run by the model and retried with feedback. effectful is reserved for commands that will need a human gate.src/cc.ts) replaces the system prompt (--system-prompt), loads no settings (--setting-sources ""), enables no tools (--tools ""), saves no session, and constrains the answer with --json-schema. This matters: a naive call once returned the operator's own email instead of the one in the input, because ambient context (global CLAUDE.md, identity, hooks) leaked in.runPipeline (src/pipeline.ts) chains commands; each step is verified before the next runs, so errors cannot silently compound.npm run scores prints per-command reliability from the CLI and eval logs, and route() (src/router.ts) shows those rates to a small model that must pick from an enum of command names.| Setting | Default | Effect |
|---|---|---|
CONDUCTOR_HOME env var | ~/.conductor | Where the MCP server appends telemetry.jsonl |
model in a manifest | sonnet | Model for that command's calls (the router and llmJudge use haiku) |
maxAttempts in a manifest | 2 | Tries with feedback before the next fallback rung (pure commands run once) |
Model-backed calls use whatever account the claude CLI is logged into.
Evals compare a single naive claude -p call with the conductor on the same inputs:
eval/run-eval.ts): baseline 100% vs conductor 100%. On easy single-shot tasks a frontier model is already reliable, so there is no gap to close.eval/contact-card.ts, extract_contact -> normalize_pho앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요