World Monitor
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 97 tools.
Spanish dialect localization MCP server: 25 regional variants, glossary, adversarial QA gates.
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Claude 暂时无法连接 DialectOS
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Claude Code 暂时无法连接 DialectOS
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VS Code 暂时无法连接 DialectOS
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它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月14日
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代码最后更新于前天
使用 Apache-2.0
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它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于前天,最新版本(0.1.0)于33天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。
同一分类中有:World Monitor, Claude Flow, Windmill
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Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 97 tools.
AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
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TL;DR: DialectOS — open-source MCP server and CLI for translating and QA-checking content across 25 regional Spanish variants. Best for AI agents, documentation teams, and app developers localizing into Spanish.
A Model Context Protocol server built specifically for Spanish dialects.
DialectOS is an open-source Spanish dialect translation server that runs as an MCP (Model Context Protocol) tool and CLI. It translates English and other languages into 25 regional Spanish variants — Mexican, Argentinian, Colombian, Puerto Rican, and more — while preserving markdown structure, enforcing glossary terms, and applying adversarial quality gates that catch semantic drift before it reaches users.
Translate, detect, and adapt content across 25 regional Spanish variants while preserving markdown structure, code comments, and locale file formatting.
📖 Documentation · 🚀 Quick Start · 🛠️ MCP Tools · Agent Skill · 📦 Packages · 🤝 Contributing · 📋 Roadmap
DialectOS is a Spanish localization and dialect QA system for AI agents, documentation teams, app developers, and support organizations. It provides MCP tools, CLI workflows, glossary enforcement, locale-file validation, and adversarial quality gates for regional Spanish variants.
AI discovery: llms.txt provides a compact project summary for AI assistants and search crawlers.
Best-fit searches: Spanish dialect translation MCP server, Spanish localization QA, Model Context Protocol translation tool, i18n validation CLI, regional Spanish translator, glossary enforcement, AI localization audit, Spanish launch certification.
DialectOS includes a public agent skill at skills/dialectos/SKILL.md. Use $dialectos in compatible agent hosts when you want an agent to choose the right MCP or CLI workflow for regional Spanish translation, markdown preservation, locale-file validation, glossary enforcement, register checks, and launch-readiness QA.
DialectOS is available as a paid Spanish localization launch audit. We certify your Spanish docs, app strings, support macros, or locale files across target dialects and deliver an MQM-aligned launch-readiness report.
audits/sample-customer-report.mddocs/spanish-launch-certification.md| Feature | Google Translate | DeepL API | DialectOS |
|---|---|---|---|
| Spanish dialect awareness | ❌ Generic "Spanish" | ⚠️ Limited variants | ✅ 25 regional variants (5 experimental, see below) |
| MCP native integration | ❌ | ⚠️ Official DeepL MCP server, generic Spanish | ✅ 18 MCP tools |
| Markdown structure preservation | ❌ | ❌ | ✅ Tables, code blocks, links intact |
| i18n locale file support | ❌ | ❌ | ✅ JSON locale diff & merge |
| Gender-neutral language | ❌ | ❌ | ✅ elles / latine / -x |
| Formality checking (tú vs usted) | ❌ | ❌ | ✅ Cross-dialect consistency |
| Adversarial quality gates | ❌ | ❌ | ✅ Semantic drift + structure validation |
| LLM-first dialect adaptation | ❌ Generic MT | ⚠️ Limited dialect control | ✅ Any OpenAI/Anthropic/LM Studio local LLM + dialect contracts |
| Translation validation (any provider) | ❌ | ❌ | ✅ `dialectos validate` — standalone correctness check |
| GitHub CI integration | ❌ | ❌ | ✅ Composite action for PR validation |
| Auto-glossary from corrections | ❌ | ❌ | ✅ Learns from user feedback |
| Public benchmark suite | ❌ | ❌ | ✅ 205 adversarial samples across 25 dialects |
Coverage is not equal across the 25 variants. es-AD, es-BZ, es-PH, es-GQ and es-US are experimental: their profiles lean on contact-language markers (Catalan, Kriol, Tagalog, English) and have thinner vocabulary and test data than the major variants.
Dialect detection is a keyword heuristic. Its last recorded top-1 accuracy was 54.8% on the bundled detection corpus, and that corpus was written from the detector's own keyword lists, so the figure is not an independent measure. Treat
detect_dialectoutput as a hint, not a verdict.
*"We shipped a product to Mexico using our Spain Spanish translations. Users thought we were being intentionally rude."*
Spanish is not one language — it's 25 regional variants with different vocabulary, formality levels, slang, and grammatical preferences. Existing translation tools treat Spanish as a monolith.
DialectOS solves this by:
Install note: DialectOS v0.3.2 is distributed as GitHub Release tarballs.
GET https://registry.npmjs.org/@kyanitelabs/dialectosandGET https://registry.npmjs.org/dialectosboth return 404 — there is no npm package. The CLI and MCP tarballs bundle the unpublished@dialectos/*workspace packages, so a singlepnpm add -g/pnpm dlxof the tarball URL works. Clone the repo only for local development or the browser demo.
Add the released MCP server to Claude Desktop, Cursor, or any MCP client:
{
"mcpServers": { "dialectos": { "command": "pnpm", "args": [ "dlx", "https://github.com/KyaniteLabs/DialectOS/releases/download/v0.3.2/dialectos-mcp-0.3.2.tgz" ], "env": { "LLM_API_URL": "https://your-llm-gateway/v1/chat/completions", "LLM_MODEL": "your-dialect-capable-model", "LLM_API_KEY": "your-key-if-required", "LLM_API_FORMAT": "openai", "ALLOWED_LOCALE_DIRS": "/path/to/locales" } } } }
ALLOWED_LOCALE_DIRS is a comma-separated list of the only directories the server may read or write; when set, it replaces the working directory. Without it the server falls back to its working directory, but never to / or your home directory, so set it when your client starts servers from either.
For local development from a source checkout, run pnpm build and point your MCP client at packages/mcp/dist/index.js.
The browser demo requires a source checkout.
The browser demo is no longer a fake/static rule replacer. It calls a local DialectOS backend, and that backend calls the configured provider stack.
LLM_API_URL="http://127.0.0.1:1234/v1/chat/completions" \
LLM_API_FORMAT="openai" \ LLM_MODEL="your-local-model-name" \ LLM_ALLOW_LOCAL=1 \ pnpm demo
Open http://127.0.0.1:8080.
For the beginner container walkthrough, see docs/full-app-demo.md.
For v0.3.0, the recommended default cloud model is glm-4.5-air through the Z.ai international Anthropic-compatible endpoint. It passed basic, expanded adversarial, and long-document certification. Use glm-5.1 when you want the higher-confidence/premium option, and qwen3.5-9b via LM Studio for local/offline certification.
export LLM_API_URL="https://api.z.ai/api/anthropic/v1/messages"
export LLM_MODEL="glm-4.5-air" export LLM_API_FORMAT="anthropic" export LLM_API_KEY="..."
Start LM Studio's local server, then point DialectOS at any downloaded local model. LLM_API_FORMAT=lmstudio uses LM Studio's native REST API and loads the model just-in-time when needed.
LM_STUDIO_URL="http://127.0.0.1:1234" \
LLM_MODEL="publisher/model-key-or-api-identifier" \ LLM_API_FORMAT="lmstudio" \ pnpm dialect:eval -- --live --provider=llm --out=/tmp/dialectos-lmstudio-eval
Use dialect:certify for long local-model or cloud-provider runs. It writes events.jsonl, progress.json, and an incrementally updated results.json after every sample, with per-sample timeout protection.
LM_STUDIO_URL="http://127.0.0.1:1234" \
LLM_MODEL="qwen3.5-9b" \ LLM_API_FORMAT="lmstudio" \ pnpm dialect:certify -- --live --provider=llm --sample-timeout-ms=300000 --out=/tmp/dialectos-certify
Use dialect:certify:adversarial to run paraphrase, dialect-collision, taboo-copy, placeholder, register, and repeatability traps. It wraps dialect:certify and writes a failure-matrix.md plus aggregate repeatability results.
pnpm dialect:certify:adversarial -- --live --provider=llm --repeat=2 --sample-timeout-ms=300000 --out=/tmp/dialectos-adversarial
Use dialect:certify:documents to certify README/API-doc/locale JSON flows, not just sentence fixtures. It checks markdown structure, placeholders, URLs, code fences, API tables, and locale JSON outputs.
pnpm dialect:certify:documents -- --live --provider=llm --dialects=es-MX,es-PA,es-PR --out=/tmp/dialectos-doc-cert
Use dialect:report to turn certification artifacts into a customer-facing Markdown deliverable for paid launch audits.
pnpm dialect:report -- --input=audits/release-candidate-2026-04-22/model-matrix.json --out=customer-report.md --customer="Acme SaaS" --product="Spanish launch"
# Install the v0.3.2 CLI tarball from the GitHub Release
pnpm add -g https://github.com/KyaniteLabs/DialectOS/releases/download/v0.3.2/dialectos-cli-0.3.2.tgz
pnpm install --frozen-lockfile pnpm build
dialectos translate "Hello world" --dialect es-MX
dialectos translate-readme README.md --dialect es-AR --output README.ar.md
dialectos validate --source "Click the button" --translated "Haz clic en el botón" --dialect es-MX
dialectos validate --source-file en.json --translated-file es-MX.json --dialect es-MX --format json
dialectos corpus stats
dialectos benchmark run --dialects es-MX,es-AR,es-ES
dialectos glossary suggest --min-occurrences 3
dialectos glossary diff glossary-v1.json glossary-v2.json
dialectos i18n detect-