scibudy 0.2.3

Codex-native scientific research expansion assistant with scholarly search, library management, and local semantic analysis

Scibudy

Scibudy is a Codex-native scientific research expansion assistant for scholarly search, library management, full-text ingestion, and local semantic analysis.

Scibudy combines:

• a local MCP server for Codex
• a shell-first CLI
• a browser management UI
• a layered install system for CPU-first and GPU-extended deployments

中文简介：

Scibudy 是一个面向 Codex 的科研增强助手，提供学术检索、文献库管理、全文分析和本地高质量语义检索能力。它既可以作为 MCP 工具，也可以作为独立 CLI 和本地管理界面使用。

Status

• License: Apache-2.0
• Release posture: stable v0.x
• Primary platforms: Linux and macOS
• Full local GPU path: Linux + NVIDIA first

Quick links

• English docs: docs/en/index.md
• 中文文档: docs/zh/index.md
• Prerequisites: docs/en/prerequisites.md / docs/zh/prerequisites.md
• Codex MCP setup: docs/en/codex-setup.md / docs/zh/codex-setup.md
• Usage examples: docs/en/examples.md / docs/zh/examples.md
• Architecture: docs/en/architecture.md / docs/zh/architecture.md
• Support matrix: docs/en/support-matrix.md / docs/zh/support-matrix.md
• Contributing: CONTRIBUTING.md
• Security: SECURITY.md
• Support: SUPPORT.md
• Roadmap: ROADMAP.md
• Changelog: CHANGELOG.md

Installation

Before you install

For most new users, the real prerequisites are only:

• Node.js 18+
• Python 3.10+

Read more:

• English: docs/en/prerequisites.md
• 中文: docs/zh/prerequisites.md

Unified installer

npx scibudy-install --profile base

Profiles:

• base: search, library management, UI, Codex config
• analysis: base + analysis-oriented runtime conventions
• gpu-local: local GPU model environment and warm flow
• full: full bootstrap for a Linux GPU workstation

Source install

git clone [e-mail]:ONEMULE/scibudy.git
cd scibudy
python3 -m venv .venv
. .venv/bin/activate
python -m pip install -e .[dev]
scibudy bootstrap --profile base --install-codex

Runtime commands

Primary command aliases:

• scibudy
• scibudy-mcp
• compatibility aliases: research-cli, research-mcp

Examples:

scibudy search "simulation-based calibration" --mode general
scibudy collect "simulation-based calibration" --target-dir ~/Desktop/sbc-library
scibudy analysis-settings
scibudy ingest-library <library_id>
scibudy search-evidence <library_id> calibration
scibudy profiles
scibudy workflow "calibration methods in simulation-based inference" --limit 50 --topic "calibration in simulation-based inference"
scibudy workflow "calibration methods in simulation-based inference" --dry-run
scibudy workflow "calibration methods in simulation-based inference" --quality-mode fast
scibudy security-audit
scibudy doctor --install-readiness
scibudy synthesize-library <library_id> "causal inference robustness" --profile general
scibudy synthesize-library <library_id> "calibration in simulation-based inference" --profile sbi_calibration
scibudy ui --open

For Codex and other agents, prefer the high-level workflow entrypoint when you want the whole research loop:

Use research/research_workflow with query="calibration methods in simulation-based inference", mode="general", limit=50, synthesize=true.

Use lower-level tools such as search_literature, collect_library, ingest_library, and build_research_synthesis when you need manual control over each step.

Use dry_run=true when an agent should preview writes and planned steps before executing. Use quality_mode=fast for low-cost exploration, standard for the normal workflow, and deep when missing full text or unsupported claims require stricter follow-up.

For safer agent automation, run scibudy security-audit and scibudy doctor --install-readiness before delegating long-running research workflows.

Domain profiles

Domain profiles do not limit Scibudy's search scope or providers. Search remains general and multi-source by default.

Profiles only tune full-text synthesis: section weighting, evidence markers, unsupported-claim detection, and risk flags.

• general: default all-domain synthesis profile.
• auto: chooses a synthesis profile from the topic while preserving general search.
• sbi_calibration: an example preset for simulation-based inference calibration workflows.

For more examples and Codex prompt patterns:

• English: docs/en/examples.md
• 中文: docs/zh/examples.md

Local model stack

The highest-quality local retrieval path currently uses:

• Qwen/Qwen3-Embedding-4B
• Qwen/Qwen3-Reranker-4B

Recommended workflow:

scibudy install-local-models
scibudy warm-local-models --background

See:

• English: docs/en/gpu-local.md
• 中文: docs/zh/gpu-local.md

Repository layout

research_mcp/   Python runtime, MCP server, CLI, analysis engine
web/            UI source and built assets
bin/            npm/bootstrap entrypoints
docs/           Bilingual project documentation
examples/       Copyable usage examples
scripts/        Release and smoke-check helpers
.github/        CI, templates, automation

Open-source project standards

This repository is intentionally organized like a professional open-source library:

• documented install profiles
• release manifest and bootstrap state
• contributor and support policies
• issue/PR templates
• CI and packaging checks
• bilingual documentation for core user workflows

Development

Core local checks:

make test
make build-ui
make package-check
make release-check

For deeper guidance:

• English: docs/en/development.md
• 中文: docs/zh/development.md