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hull — shared core for the wet / crg / mnemo self-hosted stack

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hull is the shared monorepo core for the wet, crg and mnemo self-hosted stack.

It owns everything the three products share — token auth, per-task model configuration, per-user rate limiting, local SQLite storage, the HTTP MCP server lifecycle, web scraping/search infrastructure, and a local embedding daemon — for wet (search), crg (code graph) and mnemo (memory).

Install

hull ships as one PyPI dist, n24q02m-hull. The wheel carries all three import packages; the heavy stacks are opt-in extras:

pip install n24q02m-hull               # hull_core only (crg, mnemo)
pip install "n24q02m-hull[web]"        # + hull_web scraping/browser stack (wet)
pip install "n24q02m-hull[embedding]"  # + hull_embedding_daemon server stack
pip install "n24q02m-hull[mteb]"       # + pyarrow for model_selection MTEB fetchers
pip install "n24q02m-hull[embedding,embedding-gguf]"  # + llama.cpp runtime for *-GGUF models

import hull_web without the [web] extra raises ImportError naming the missing modules and the install command.

The TypeScript core ships to npm as @n24q02m/hull, at the same version as the PyPI dist (see packages/core-ts):

npm install @n24q02m/hull

Packages

Source dir Import package Extra Purpose
packages/core-py hull_core (base; MTEB boards need [mteb]) Auth (3 modes), per-task model cells, limiter, ~/.hull/ SQLite WAL storage, server start + /mcp endpoint, CLI, SSRF-safe HTTP, lifecycle lock, model_selection leaderboard picker + runtime registry (refresh → eval-on-change → promote)
packages/embedding-daemon hull_embedding_daemon [embedding] Local ONNX/GGUF embedding server (FastAPI)
packages/web hull_web [web] Search (SearXNG), scraping strategies, stealth browsers, fingerprinting, HTTP/SSRF security
packages/core-ts @n24q02m/hull (npm) n/a TypeScript core: MCP Streamable HTTP transport, OAuth 2.1 authorization server, credential storage, relay client

Runtime model

  • Python 3.13. Dev with uv, always-on with docker.
  • hull server start is the only way to run a server; MCP is an HTTP endpoint at http://host:port/mcp — never a spawned subprocess.
  • The CLI is the control plane + consumer. With the server down the CLI tells you to start it first; there is no hidden local-core mode.
  • Provider calls are plain OpenAI-spec HTTP (httpx). OpenRouter is the pre-wired default. Each task (embed, rerank, chat, jev_score) has its own base_url + api_key + model cell — change provider by editing config, never code.
  • Storage is local SQLite (WAL) under ~/.hull/. Backup/sync is rclone outside this repo.

Auth — one mechanism, three modes

Mode is a config state ([server] auth in ~/.hull/config.toml):

  1. no-auth — localhost-only bind enforced, one shared namespace.
  2. token — one shared token (token_hash in config), still one shared namespace.
  3. multi — users.toml maps uid → {token_hash, enabled, namespace, allowed_roots, limits}; one process serves N users, each isolated to their namespace. Admin is host-side only: edit users.toml, restart.

Token hashes are scrypt (hull token hash). Wrong token → 401; disabled user → 403; over-limit → 429.

Quick start

uv sync
uv run hull config init          # write ~/.hull/config.toml (OpenRouter defaults)
uv run hull token hash mysecret  # mint a token_hash for users.toml / config
uv run hull server start         # serves http://127.0.0.1:8000/mcp

Development

uv sync --all-extras
uv run pytest -q
uv run ruff check .
uv build

License

Apache-2.0

Metadata

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