conductor

Name: conductor
Author: fainir

by fainirversion 0.4.1i★ –iRuns on your computer

Registry nameio.github.fainir/conductor

Install

Overview

Description from the maker (original English)

Verified tool calls for Claude Code: verify, retry and fallback over hermetic claude calls.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "conductor": {
      "command": "npx",
      "args": [
        "-y",
        "@fainir/conductor"
      ]
    }
  }
}

Run this in your terminal

claude mcp add conductor -- npx -y @fainir/conductor

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "conductor": {
      "command": "npx",
      "args": [
        "-y",
        "@fainir/conductor"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "conductor": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@fainir/conductor"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account fainir, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32484 servers in this category
Published to the registry more recently than 81% of the other 32484 servers in this category
Basic checks equal to or better than 100% of the other 32484 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is conductor safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.4.1) reached the registry 8 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Recta

Alternatives

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

conductor

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.

Quick start

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.

Usage

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.

Tools

Pure tools (code only, no model call)

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

Model-backed tools (hermetic `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.

How it works

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)

Contracts with mandatory verifiers. Each command is 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.
Precondition gate. Input that breaks the command's inputSchema is rejected before anything runs, with a message that names the problem.
Determinism gradient. 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.
Fallback to freeform. Every model-backed ladder ends at plain Claude, held to the same output schema and verifier, so the conductor never does worse than a raw call, only better when a verified command applies.
Hermetic calls. Every model call (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.
Composition. runPipeline (src/pipeline.ts) chains commands; each step is verified before the next runs, so errors cannot silently compound.
Telemetry and routing. Every attempt is a JSONL line. 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.

Configuration

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.

Results (measured by the author)

Evals compare a single naive claude -p call with the conductor on the same inputs:

Single-shot extraction (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.
Composition (eval/contact-card.ts, extract_contact -> normalize_pho

Only the beginning is shown; read the rest in the repo

conductor

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Recta

README from the maker

conductor

Quick start

Usage

Tools

Pure tools (code only, no model call)

Model-backed tools (hermetic claude -p call)

How it works

Configuration

Results (measured by the author)

Model-backed tools (hermetic `claude -p` call)