Logic Server runs on your own machine — the client starts it, so there is no endpoint to ping. 60 installs a week from npm. Last commit 14 Aug 2026.
Agent reasoning, memory, and token-optimized context for AI applications.
We read the source, 20 h ago · rules 3dff92dd89df
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.
java.io.File("/.dockerenv").exists() ||
этот файл ставится пользователю, но в репозитории его нет
Runtime.getRuntime().exec(arrayOf("bash", "-c", "docker compose version >/dev/null 2>&1")).waitFor() == 0 -> "docker compose"
Ctrl+W Delete word
Ctrl+R (coming soon) reverse search
q / exit Quit
${DIM}exec / dsl = raw DSL h / help = this message${RESET}
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
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.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add logic-server -- npx -y nocturnusai-mcp
{
"mcpServers": {
"logic-server": {
"args": [
"-y",
"nocturnusai-mcp"
],
"command": "npx"
}
}
}
[mcp_servers.logic-server]
command = "npx"
args = ["-y", "nocturnusai-mcp"]
{
"mcpServers": {
"logic-server": {
"args": [
"-y",
"nocturnusai-mcp"
],
"command": "npx"
}
}
}
{
"mcpServers": {
"logic-server": {
"args": [
"-y",
"nocturnusai-mcp"
],
"command": "npx"
}
}
}
This one needs environment variables set before it will start:
NOCTURNUSAI_URL (Base URL of the NocturnusAI server), NOCTURNUSAI_API_KEY (API key for authenticated access), NOCTURNUSAI_DATABASE (Database name to use), NOCTURNUSAI_TENANT (Tenant ID for multi-tenant isolation).
The author declared them in the registry entry; get the values from the project itself.
Govern model, retrieval, memory, and tool access for AI applications and agents.
19 focused API tools for AI agents: contract review, prompt optimizer, context packing, and more.
Memory that reasons: continual learning for stateful agents. Better context, fewer tokens.
Persistent memory for AI agents — log and recall conversation context over MCP.
Memory, docs, and repo context layer for engineering agents.
Search and list applications for AI agents. Remote MCP on b0tl1nk.com.
Token-bounded repository context for coding agents over MCP.
Encrypted mail, shared memory, and persistent context for AI agents.
Answers built from our own checks of this server.