Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
Serves the Alchemy writing ruleset to any agent, so its prose loses the usual LLM tells.
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 …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"alchemy": {
"command": "npx",
"args": [
"-y",
"@fernforge/alchemy-mcp"
]
}
}
}Run this in your terminal
claude mcp add alchemy -- npx -y @fernforge/alchemy-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"alchemy": {
"command": "npx",
"args": [
"-y",
"@fernforge/alchemy-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": {
"alchemy": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@fernforge/alchemy-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.
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.
Runs on your computer; the tool list appears in your AI app after you install it.
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
The registry name was verified with the GitHub account fernforge, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
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 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).
The GitHub repo last changed –, and the latest version (0.1.1) reached the registry 4 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Context7, Codebase Memory, Exa
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
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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.
Alchemy is a drop-in ruleset that stops your AI coding agent from writing like an LLM: no em-dash pile-ups, no "not just X, it's Y", no stray *delve*. You add it once, your agent reads it before it writes, and the READMEs, commits, and docs it produces start sounding like a person wrote them.
Turn lead into gold. It's one file, about 1000 tokens, that lives next to your agent's other instructions: ALCHEMY.md. Everything else here just gets it into your project.
Install it in your project and point your agent at it. Pick whichever fits your stack:
# Node / npm
npx @fernforge/alchemy init
pip install alchemy-writing alchemy init
init writes ALCHEMY.md into your project and links it from whatever agent config you already have: CLAUDE.md, AGENTS.md, .cursorrules, or Copilot instructions. From then on the agent reads the rules as part of its normal context. To print the ruleset to stdout without installing anything:
npx @fernforge/alchemy print # or: alchemy print
Prefer to do it by hand? Copy ALCHEMY.md into your repo and reference it from your agent's instruction file. That's the whole mechanism. No service, no API, no account.
Here's the kind of sentence Alchemy catches. Same fact, two ways of saying it:
Before
Redis isn't just a database — it's a powerful, robust caching layer that unlocks the full potential of your entire stack.
After
Redis is an in-memory store. Put your cache and sessions in it and your database stops being the bottleneck.
The "before" stacks four tells in one sentence: the "isn't just X, it's Y" non-contrast, the adjective pile (powerful, robust), the lone dramatic em-dash, and "unlocks the full potential". None of it says what Redis does. The "after" drops all of it and states one concrete thing you can act on. That's the whole move, applied everywhere the agent writes.
The concrete ones, by name:
The fix is never a synonym swap. It's replacing the vague word with a specific fact: not "robust" but "handles 10k req/sec". The rules push the agent toward the fact.
The principle underneath: no single word proves a machine wrote something. The signal is many of these clustered together over flat, evenly-weighted text. Alchemy targets the clustering, so it thins the tells without stripping a word that's genuinely the right one.
init detects the config files already in your project and links the ruleset from them, so the same ALCHEMY.md works across agents:
CLAUDE.md..cursorrules.AGENTS.md picks it up there.One ruleset, whichever agent you're driving.
To serve the rules on demand across every project instead of committing a file to each repo, run Alchemy as an MCP server. Add it to your client config (Claude Desktop, Cursor, Cline):
{
"mcpServers": { "alchemy": { "command": "npx", "args": ["-y", "@fernforge/alchemy-mcp"] } } }
It exposes a get_writing_rules tool and an alchemy://rules resource, so any MCP-aware agent can pull the ruleset when it's about to write prose. See mcp/ for details.
All three ship the same rules from the same source, so pick by your toolchain and mix freely:
@fernforge/alchemy — npx @fernforge/alchemy initalchemy-writing — pip install alchemy-writing@fernforge/alchemy-mcp — npx @fernforge/alchemy-mcpThey're grounded in what people actually flag as AI writing, not guesses: Wikipedia's "Signs of AI writing", the Kobak et al. study measuring which words spiked in research papers after ChatGPT, Pangram's phrase-frequency data, and the long-running arguments on Reddit and in r/Professors about spotting it. It's kept short on purpose: concrete guidance an agent can hold in context, not an essay.
This README follows its own rules. If it reads fine, that's the pitch.
Found a tell it misses? Open an issue or a PR with a real before-and-after pair. Concrete examples are worth more than new abstract rules.
Edit the root ALCHEMY.md only. The copies under python/ and mcp/ are generated from it by node scripts/sync-rules.mjs, and CI fails if they drift. The npm, PyPI, and MCP packages publish from GitHub Releases (see .github/workflows).
MIT