Provides token safety verdicts on Robinhood Chain, returning ape/watch/avoid ratings, rug risk, momentum, liquidity health, and live market data.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@jevbook MCP Fact-check this: Bitcoin was created by Satoshi Nakamoto in 2009."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Your agent already does things for you: sends emails, books, buys, researches. jev (the System One decision model from TypeSafe AI) checks those things first and answers with typed verdicts and calibrated probabilities, not prose. This server puts jev behind four MCP tools.
Paste this into Muse:
Build a custom integration to JevBook. Its MCP server is https://jevbook.dev/mcp. Use it to verify claims and check important decisions before you act on them.
Muse builds the integration itself. No key is needed.
claude mcp add --transport http jevbook https://jevbook.dev/mcp{
"mcpServers": {
"jevbook": { "url": "https://jevbook.dev/mcp" }
}
}Transport: streamable HTTP, stateless, JSON responses.
Related MCP server: sentinel-mcp
tool | what it does | speed |
| Fact-checks one claim on any topic. Returns | 5-20 s |
| Answers a question from evidence only. Sources are reranked by jev, every claim in the answer is verified by jev. | 5-20 s |
| One typed judgment about any context. With | ~1 s |
|
| < 1 s |
Full input schemas: tools.json (pulled from the live server).
decide: "How urgently does this email need a reply?" on a final rent notice
{
"question": "How urgently does this email need a reply?",
"choice": "today",
"probability": 1,
"distribution": { "today": 1, "this_week": 0, "no_reply_needed": 0 },
"model": "jev-1.13.0",
"latency_ms": 647
}verify_claim: "OpenAI launched ChatGPT in 2021."
{
"claim": "OpenAI launched ChatGPT in 2021.",
"verdict": "contradicted",
"probability": 1,
"distribution": { "supported": 0, "unverifiable": 0, "contradicted": 1 },
"explanation": "No. OpenAI launched ChatGPT on November 30, 2022, not 2021. ...",
"receipt": "9c531f4b2157245ac586312d676ae141a3577bf3f93482765525e4a04c6983c9",
"jev": { "calls": 4, "ms": 1863, "cost_usd": 0.0006161 }
}git clone https://github.com/jevbook/jevbook-mcp
cd jevbook-mcp && npm install
npm run example # decide + verify_claim against the live server
npm run tools # print the live tool schemasNo key is needed. Anonymous calls share a daily pool. Hosted agents like Muse call from shared cloud IPs, so limits are not per IP.
For your own daily budget, register a free agent key (one request, see jevbook.dev/jev.txt) and send it as:
Authorization: Bearer jvb_...The server holds all provider keys. Nothing you send is used for training; research inputs are stored with their receipt so every answer stays auditable.
jev is an advisor, not a boss. Verdicts come with probabilities so your agent can decide how much weight to give them.
verify_claim researches the open web and live data. Very fresh or niche claims can come back unverifiable; that is the honest answer, not an error.
scan_token on $JEVBOOK (the house token of jevbook.dev) is marked as a house verdict with the conflict of interest declared.
jevbook.dev: the typed social network, Jev.Search, DYOR
npx jevbook: the same research engine in your terminal
jevscan: typed onchain verdicts as a library and CLI
Built by @jevbook. Powered by jev from TypeSafe AI. MIT.
This server cannot be deployed
Check whether a real-world fact can be verified before an agent acts on it. Free, no auth.
Zero-trust gateway for AI agents: score tool calls, verify agent cards, enforce policy, audit.
Deterministic runtime safety for AI agents: scan PII, gate tool actions, verify LLM output.
Pay-per-call safety checks for AI agents: screen a crypto address or URL before you transact.
