AI advisory board (MCP): quotes verified word-for-word against public-domain texts, fail-closed
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io.github.ilyautov/consilium-principis is an MCP server that AI advisory board (MCP): quotes verified word-for-word against public-domain texts, fail-closed. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 92/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"io-github-ilyautov-consilium-principis": {
"args": [
"-y",
"skills"
],
"command": "npx"
}
}
}Are you the author?
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A personal board of several AI advisors — for decisions where one confident answer isn't enough.
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A personal board of several AI advisors — for decisions where one confident answer isn't enough.
Live: a made-up "Aurelius quote" is refused; a real line is confirmed 🔵 word-for-word with its source. The verdict is computed by code on every run, not scripted.
Each advisor looks through their own lens, argues with you and with the others, and the board converges on a single next step. But above all: Consilium doesn't pass off a plausible fabrication as the author's words — a 🔵 quote is checked by code against the source text word-for-word; with no exact line in the corpus, the advisor simply doesn't quote.
Consilium Principis is a skill and MCP server for AI agents. You connect it to your agent, ask a question you need to decide on, and it gathers a board around the table: Sun Tzu, Marcus Aurelius, Machiavelli, Epictetus, and whoever else you add. Each looks at it through their own lens, leans on their own texts, and argues — with you and with the others. At the end you get one synthesis and one next step. And if the question is quantifiable ("which is more worthwhile, X or Y"), the board doesn't eyeball it — it breaks the decision into numbers and runs them through a Monte Carlo.
This project doesn't ask an AI to roleplay a sage — we tried to build a tool, not a roleplay game or an aphorism generator. Why you can trust its quotes comes next.
One honest thing about who's at the table: these aren't the thinkers themselves but their AI versions — a prism of their views over the corpus of their public texts. Nobody is "speaking from beyond the grave." An advisor holds the author's lens and leans on their words, but it stays a model — and we say so plainly.
No extra keys or payment — Consilium runs on the agent you already have. Checking quotes needs no internet; a full offline setup just takes local models.
The "several AIs deliberate" mechanic is already common. What sets Consilium apart isn't the number of voices. It's that a claim can be re-verified, and where it can't, the council honestly stays silent:
| "Roleplay a sage" (one AI) | LLM-Council-style board | Consilium | |
|---|---|---|---|
| Different lenses, disagreement as a feature | ± | ✅ | ✅ |
| Verbatim quote checked word-for-word against the original, with its source | ✗ | ✗ | ✅ |
| Honestly silent outside the corpus (fail-closed) | ✗ | ✗ | ✅ |
| Quantifiable question → Monte Carlo (📐) | ✗ | ✗ | ✅ |
| No extra keys or payment | ± | ✗ | ✅ |
A "personal board of directors" is a mainstream practice (an HBR concept); the bet on grounding and citation transparency has been validated by both the market (Delphi, $16M from Sequoia) and academia (multi-persona debate, the ALCE benchmark). Our angle is rigor: a verifiable quote and an honest refusal.
The refusal + word-for-word verification is in the demo up top. More scenarios — wrong-mouth attribution, Monte Carlo, cross-lingual: demo gallery →
You ask in plain words:
**"I'm juggling four directions at on