Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Turn an English food description into an EFSA FoodEx2 code.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Works in Claude on the web, desktop and mobile:
https://foodex2-encoder.foodnotes.org/mcpRun this in your terminal
claude mcp add --transport http foodex2-encoder https://foodex2-encoder.foodnotes.org/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"foodex2-encoder": {
"url": "https://foodex2-encoder.foodnotes.org/mcp"
}
}
}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.
Paste into .vscode/mcp.json in your project
{
"servers": {
"foodex2-encoder": {
"type": "http",
"url": "https://foodex2-encoder.foodnotes.org/mcp"
}
}
}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.
ChatGPT connects only to servers on the internet:
https://foodex2-encoder.foodnotes.org/mcpMenu names can differ slightly by plan and over time.
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.
We have not read this server’s tool list yet; we check endpoints in rotation.
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 7, 2026
The registry name was verified against the domain foodnotes.org (the registry checks domain ownership)
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
Not checked yet; we check endpoints in rotation
Not checked yet; we check endpoints in rotation
Not checked yet; we read the tool list when we check the endpoint
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 21 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Spec Driven Development, Remote Desktop Commander, sync. labs
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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.
Lipsync videos, dub them into other languages, make talking videos and open sync. Studio.
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.
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: