Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Turn an English food description into an EFSA FoodEx2 code.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
适用于网页版、桌面版和手机版 Claude:
https://foodex2-encoder.foodnotes.org/mcp在终端中运行这条命令
claude mcp add --transport http foodex2-encoder https://foodex2-encoder.foodnotes.org/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"foodex2-encoder": {
"url": "https://foodex2-encoder.foodnotes.org/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"foodex2-encoder": {
"type": "http",
"url": "https://foodex2-encoder.foodnotes.org/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
ChatGPT 只能连接互联网上的服务器:
https://foodex2-encoder.foodnotes.org/mcp菜单名称可能因套餐和版本不同而略有差异。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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7日
注册名称已通过域名 foodnotes.org 验证(注册中心会核实域名所有权)
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.0.0)于21天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Detailing Manager
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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.
Connect your auto detailing studio's tasks, cars, clients and revenue to Claude or ChatGPT.
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Library and stdio MCP server that turns an English food description into an EFSA FoodEx2 code (MTX catalogue): base term, facet descriptors, and labelled free text for what the code cannot express.
This repository is the core. A hosted version is available at https://foodex2-encoder.foodnotes.org/ .
Check every code before you use it. In particular:
source-commodity=shellfish in free text, rather than *Canned seafood* made from crustaceans and molluscs. The code is not wrong, but it is broader than the description: *Canned seafood* also covers other marine animals, such as sea urchins..ecf)git clone https://github.com/FoodNotes-org/foodex2-encoder.git
cd foodex2-encoder git submodule update --init npm install npm run build:catalogue npm run build:embeddings
data/ is generated locally (~25 MB) and is gitignored. Rebuild after updating the vendor/efsa-catalogues submodule.
The coding rules in src/rules/ (EFSA business rules, facet cardinality, our own checks) are shared with the FoodEx2 Atlas validator. Their data comes from rules/cardinality.yaml, rules/conflicts.yaml and vendor/efsa-business-rules/; after editing those, regenerate the committed src/rules/rules-data.json with npm run build:rules. Sources, licence and limits are in rules/efsa-business-rules.md.
Copy .env (or export the same variables). OpenRouter needs only a key:
FOODEX2_LLM_API_KEY=sk-or-… # or OPENROUTER_API_KEY
Any other OpenAI-compatible endpoint works the same way (FOODEX2_LLM_BASE_URL, FOODEX2_LLM_API_KEY, FOODEX2_MODEL). The server calls that endpoint for classify / select / residual steps; your chat client’s subscription is separate.
npm run cli -- encode "orange juice"
npm run cli -- encode "fried rice with chicken" npm run cli -- traverse "eggplant" # walk only (debug)
Lexical hits return in about a second. Descriptions that need a catalogue walk typically take 15–25 seconds.
npm run server
Point a client at that process. Cursor example (mcp.json):
{
"mcpServers": { "foodex2-encoder": { "command": "npx", "args": ["tsx", "/ABS/PATH/TO/foodex2-encoder/src/server.ts"], "env": { "FOODEX2_LLM_API_KEY": "sk-or-…" } } } }
Tool: encode. It returns the code, base term, facets, free text, fit, method, and a short explanation. Catalogue lookups, decoding, validation and EFSA guidance are in the free FoodEx2 Atlas MCP.
npm test # unit tests (no model)
npm run lexical-eval # lexical base-term cases (no model) npm run encode-eval # end-to-end gold set (needs a model key)
eval/encode-base-term.yaml is a small, focused regression set: one realistic case per capability (catalogue synonym, model synonym, named dish, restraint, and so on). Gold rules can require or forbid facets and free-text fragments; expected may list several acceptable base codes (any-of).
npm run encode-eval records the model and MTX version, and on a complete run writes eval/results/encode-base-term.json for publishing or sharing with the public core repo. Always cite the model named in that file’s _provenance.
src/encode/ lexical → traverse → select → residuals
src/search/ lexical + embedding retrieval src/server.ts stdio MCP src/tools.ts tool handlers (shared surface for a future Worker wrapper) data/ generated catalogue + embeddings (local) eval/ gold cases + results artifact vendor/ EFSA catalogues (submodule)
MIT — see LICENSE. Copyright (c) 2026 e-accent BV.
That grant covers this software. EFSA catalogue files under vendor/efsa-catalogues/ (and generated data/ derived from them) remain subject to EFSA’s terms.
Some food names used as evaluation cases under eval/ were drawn from national food composition databases. We use food names only (not nutrient values). Those databases remain under their publishers’ terms: