Mindjack MCP Server

by mindjack Your server? Claim it

answering

Mindjack is answering right now. Last checked 16 min ago. 82 installs a week from npm. It exposes 26 tools. Last commit 1 Sep 2026.

Solana memecoin rug check for trading agents: pump.fun launches, calibrated rug risk, wallets, KOL.

Installs per day peak 698 · avg 75 · -55% w/w

a month agotoday

Uptime history 32 days of history

32 days agonow

100.0%

Uptime 24h

91 of 91 checks

Tools

read from the server

192 ms

Response time

average over 24h

Installs / week

npm and PyPI

What changed 137

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 18 August 2026. No other catalogue keeps this.

1 Sep a tool description was rewritten test_hypothesis

1 Sep a tool changed version

21 Aug 20 tool descriptions were rewritten33 times that day can_i_exit, check_token, check_wallet and 17 more

21 Aug a tool changed version4 times that day

19 Aug 2 tools appeared fetch, search

19 Aug a tool changed version

18 Aug 24 tools changed the parameters they ask for66 times that day can_i_exit, check_token, check_wallet and 21 more

18 Aug 24 tool descriptions were rewritten can_i_exit, check_token, check_wallet and 21 more

18 Aug a tool changed version5 times that day

and 62 more, back to 18 August 2026

What the code does

We read the source, 18 h ago · tools taken from the live server · rules 3dff92dd89df

Capabilities

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

Runs an external command test-release.mjs:13

const child = spawn(process.execPath, ["src/index.js"], {

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

This code can reach further than it looks

We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 16 min ago.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add mcp --transport http https://api.mindjack.xyz/mcp

~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "mcp": {
      "url": "https://api.mindjack.xyz/mcp"
    }
  }
}

~/.codex/config.toml

[mcp_servers.mcp]
url = "https://api.mindjack.xyz/mcp"

.cursor/mcp.json

{
  "mcpServers": {
    "mcp": {
      "url": "https://api.mindjack.xyz/mcp"
    }
  }
}

.vscode/mcp.json

{
  "mcpServers": {
    "mcp": {
      "url": "https://api.mindjack.xyz/mcp"
    }
  }
}

Available tools 26

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

token

check_token

[$0.001] Is this Solana token dangerous? A calibrated rug verdict whose probability is a MEASURED frequency (see get_scorecard), the concentration facts behind it, and how fast this band tends to collapse. Cheapest call, run it on every token; it decides whether inspect_token, token_identity or token_report is worth paying for. Does not name holders.

token_changes

[$0.025] Who sold since we analysed it: reads the chain now and diffs the large positions against what we recorded. Use when a cached read feels stale or to see whether concentrated wallets are exiting. The only call that touches the chain live.

token_graph

[$0.04] The wallet relationship graph behind a token: edges with strength and confidence, cluster membership and role, wash-trading wallets. token_wallets names the holders; this shows how they are CONNECTED and whether a distributed-looking set is one person. Not a first look.

token_identity

[$0.025] Who is BEHIND this token: what its largest holders did in earlier launches, which sibling tokens the same wallets ran and how those ended, and the measured upside band. The decision-point call. Coverage is reported per call; an empty result is free.

token_price_path

[$0.005] What the token did after we called it: peak, drawdown from peak, and where it stands now, at 4-5 second resolution. Our feed starts at analysis; the bonding-curve phase before that is not included.

token_report

[$0.025] check_token + inspect_token + token_identity in one call. depth="full" ($0.07) adds the outcome path, live sellability and the wallet graph. Cheaper than the parts; use once a token is worth a real look. `fetch` is this call under the name ChatGPT requires.

token_wallets

[$0.005] The NAMED wallets behind one token: insiders, snipers, early buyers, fresh wallets, wash traders and tracked KOLs, each with funder (exchanges named), link count and cluster. Lists cap at 100 per class; *_total fields carry real counts. inspect_token gives counts, this gives addresses.

token_web

[$0.04] Earlier launches tied to this token through shared wallets, with the wallets themselves, each launch's outcome and its highest recorded market cap. Use when token_identity reported shared wallets and you need WHICH launches. token_graph stays inside one token; this crosses tokens.

kol

kol_leaderboard

[$0.02/page] Every tracked KOL wallet, ranked from the recorded trades: lifetime realized SOL, per-token win rate on NET realized SOL, and a recent-activity window. Sort by profit, success or activity. Use to build or refresh a copy-trading watchlist.

kol_record

[$0.02] One tracked KOL in depth: lifetime stats, per-token history from every recorded trade (buys, sells, volume, realized SOL) and the latest trades raw. Untracked addresses answer null and cost nothing; check_wallet covers any wallet.

tokens

find_tokens

[$0.005] Recently analysed tokens, each already carrying a verdict, to rank locally before paying for depth. Filters: hours (1-168), min_mcap, platform, limit (1-100). A time-ordered feed with no query; to find a token you know by name or mint, use search_tokens.

search_tokens

[$0.005/page] Find a token in the analysed catalogue by symbol, name fragment or exact mint, with platform, size and age filters. find_tokens lists what just migrated; this finds the one you mean. `search` is the same call in the shape ChatGPT requires.

wallet

check_wallet

[$0.006] One wallet across every token we indexed: launches it appeared in, how many ran, roles it recurs in, realised record. Works for any address. kol_record is the per-trade history of tracked KOLs; wallet_network is who this wallet moves with.

wallet_network

[$0.025] Who one wallet is wired to across the index: direct counterparts with interaction counts, shared tokens, transfer direction where the chain shows it, plus a bounded second hop. check_wallet says what it DID; this says who it MOVES WITH.

balance

get_balance

[free] Credits remaining on your key. There is no free allowance: a new key starts at zero and is funded with a USDC deposit, so a balance of 0 means the paid tools will answer 402 until you top up.

can

can_i_exit

[$0.005] Can this token be sold RIGHT NOW, and what does a round trip cost: real Jupiter buy and sell routes at $100 and $1000, and the fraction of your money that survives. Verdict follows the worst rung: clear / elevated / thin / trapped / blocked. Quotes only, nothing is signed; not cached, takes a few hundred ms.

compare

compare_tokens

[$0.025] Were these tokens run by the same people? Give 2-4 mints and get the wallets appearing in more than one, each with the role it played in each. Weigh the roles rather than the count: shared holders are common, a wallet that was an insider in one and a sniper in the next is not. Mints outside our index come back named in not_covered.

coverage

get_coverage

[free] What we hold and how fresh, plus a live example mint guaranteed to have data. Call this first: we index every pump.fun and letsbonk migration since our start date, so an older token you already know will return nothing.

fetch

fetch

[$0.025] ChatGPT entry point: everything we hold on one token as one document: the calibrated verdict with its measured hit rate, who holds it and how they connect, and whether it can still be sold. Takes an id from `search`. Same endpoint and price as token_report, which other clients should call.

funder

funder_networks

[$0.025/page] Funders ranked by how many fresh wallets they seeded across the whole index, each labelled when we know the exchange behind it. A funder inside one token is a line item; across the index it is a desk. A null label with a high count is the shape worth opening.

inspect

inspect_token

[$0.005] Who is involved: top holders and supply, the sniper / fresh-wallet / insider / early-buyer split, connected-group topology, tracked-trader activity. Counts and structure only: token_wallets names them, token_graph draws the edges, token_web follows them to earlier launches.

sample

get_sample

[free, no key] One fixed token answered in full: the complete check_token, inspect_token and token_identity responses, each carrying the price that call costs. Served by the same handlers as the paid tools, so it is what you would actually get. Use get_coverage for freshness, this for depth.

scorecard

get_scorecard

[free] Our measured hit rate per risk band, and how fast each band tends to collapse. Read this to decide how much weight to give our verdicts. Most risk APIs ask you to trust a score; this one shows how it performed.

search

[$0.005/page] ChatGPT entry point: the same catalogue search as search_tokens (same endpoint and price) returning {id, title, url} rows, each id a Solana mint for `fetch`. ChatGPT connects to nothing without this exact name; other clients should call search_tokens.

serial

find_serial_insiders

[$0.025 per 25] Wallets that keep turning up as insiders across the whole index. Each row carries the wallet's full footprint, because ranking on insider count alone puts bots on top (the highest is flagged in 1,642 tokens and holds 4,091). Read insider_in against also_held: close is a real serial insider, far apart is a bot.

test

test_hypothesis

[$0.025] Measure what happened to every indexed launch matching your filters: rug rate against the index base rate, peak-gain percentiles, time to peak, collapse speed. Answers pattern questions like 'do launches with under 200 holders die faster?'; to shortlist live tokens to act on, use find_tokens instead. filters is {field: {min,max}} over numeric fields listed by get_coverage, e.g. {total_holders: {min: 200}}. Returns cohort aggregates and a one-sentence finding, never per-token rows. Read-only over stored history; measured past, not a forecast.

Endpoints

URL	Transport	State	Latency	Checked
https://api.mindjack.xyz/mcp	streamable-http	answering	219 ms	16 min ago

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Mindjack — questions

Answers built from our own checks of this server.

What can Mindjack do?

It exposes 26 tools, read directly from the server on our last check. Among them: can_i_exit, check_token, check_wallet, compare_tokens, fetch, find_serial_insiders and 20 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →

What is Mindjack mostly used for?

Its tools cluster around token, kol and tokens. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.

Is Mindjack working right now?

We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 192 ms. The bar chart above shows every period we have measured.

How do I connect Mindjack?

Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.

Does Mindjack need an API key?

No. Mindjack completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 26 of them are readable on this page. This is what we observed, not what the docs claim.

How fast is Mindjack?

It answers our handshake in 192 ms on average, which is faster than 68% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.

How many people use Mindjack?

The npm package @mindjack/mcp was installed 82 times in the last week. Week over week that is -55%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.

Is Mindjack open source?

Yes — it is published under the MIT licence, written in JavaScript and 3 stars on GitHub. The source link is on this page, so you can read exactly what it does with your data before you connect it.