
Alchemy
io.github.fernforgePublished by GitHub account fernforgev0.1.1Updated Oct 24, 2026
Serves the Alchemy writing ruleset to any agent, so its prose loses the usual LLM tells.
The publisher's own server: Alchemy MCP Server
Overview
Serves a writing ruleset that steers an AI assistant away from common LLM prose tics when it drafts documentation, commits, or other text.
- What you can do
- Alchemy exposes a get_writing_rules tool and an alchemy://rules resource that return a short ruleset (about 1000 tokens) describing LLM writing tells to avoid: empty contrasts, stacked adjectives, em-dash pile-ups, filler vocabulary, and throat-clearing openers. An agent can pull the rules before writing prose so its READMEs, commits, and docs read more plainly. The same ruleset is also distributed as a file that can be linked from agent instruction files.
- When to use it
- Worth adding when an assistant regularly writes prose in your projects and you want its output to avoid recognizable LLM phrasing. Useful if you prefer serving the rules on demand across projects rather than committing a rules file to each repository.
- Requirements
- Runs locally over stdio as the npm package @fernforge/alchemy-mcp, so Node.js and npx are needed. No account, API key, or environment variable is declared.
Installation
In SourceWeft
- Open Alchemy in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
[Alchemy — write like a human, not an LLM]
Alchemy
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.
How do I stop my AI from writing like an LLM?
Install it in your project and point your agent at it. Pick whichever fits your stack:
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:
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.
Before and after
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.
Which LLM tells does it remove?
The concrete ones, by name:
- Empty contrasts: "not just X, it's Y", "it's not about A, it's about B".
- Staccato trios and rule-of-three padding: "fast, reliable, scalable", "No X. No Y. Just Z."
- Stacked adjectives standing in for facts: robust, seamless, powerful, comprehensive.
- Em-dash pile-ups. The real tell is density, so the rule is: use them rarely.
- Filler vocabulary: delve, leverage, harness, unlock, elevate, tapestry, realm, showcase.
- Throat-clearing openers ("In today's fast-paced world", "At its core") and recap closers ("In conclusion", "Ultimately").
- Restating the prompt before answering it.
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.
Use it with Claude, Cursor, or Copilot
init detects the config files already in your project and links the ruleset from them, so the same ALCHEMY.md works across agents:
- Claude Code / Claude reads it via
CLAUDE.md. - Cursor reads it via
.cursorrules. - Copilot reads it via its instructions file.
- Any agent that supports
AGENTS.mdpicks it up there.
One ruleset, whichever agent you're driving.
Use it as an MCP server
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):
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.
Three ways to install, one ruleset
All three ship the same rules from the same source, so pick by your toolchain and mix freely:
- npm:
@fernforge/alchemy—npx @fernforge/alchemy init - PyPI:
alchemy-writing—pip install alchemy-writing - MCP:
@fernforge/alchemy-mcp—npx @fernforge/alchemy-mcp
Where the rules come from
They'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.
Contributing
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).
License
MIT
Source: README.md at commit 83e5eec
Tools
0Version history
1- v0.1.1LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts
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