Open Source
We ship the stack in public.
Five open-source projects from Neura Parse. Permissive licences, no telemetry, built to be forked and shipped. Some are research companions; others are the daily tools we run on ourselves.
5
Public projects
20+
GitHub stars
MIT / Apache-2.0
Permissive licences
0
Telemetry
Why we open-source
Three categories, one principle.
We open the layers where customers benefit from inspectability, and we keep proprietary the layers where customers pay for hard-won engineering.
Developer tools
Local-first software for engineers who already have an editor and a terminal. Designed to plug into existing workflows, not to replace them.
Productivity
Self-hosted alternatives to closed SaaS. Bring your own database, your own keys, your own infrastructure — keep your data where it belongs.
Quantum research
Reference libraries that accompany our published research. Apache-2.0, designed for academic citation and partner integration, not for vendor lock-in.
Compare
All five projects, side-by-side.
Sort by stars, language, status, or filter by category. The detailed cards below dive into capabilities and the install path.
| Category | Licence | Links | ||||
|---|---|---|---|---|---|---|
| TaskNebula Self-hosted PM with AI copilot — Linear UX × Jira scale × pair-programmer AI. | Productivity | Stable | TypeScript | MIT | 16 | |
| QMANN Quantum-memory networks · 3 reproducible modes (Theoretical / Simulation / Hardware). | Quantum research | Beta | Python | Apache-2.0 | 3 | |
| qmesh Modality-agnostic IR for gate, neutral-atom, photonic-CV and pulse — FT-mode is one flag. | Quantum research | Public preview | Python | Apache-2.0 | 1 | |
| NeuraBar macOS menu-bar workspace — 8 tools, 11 coding CLIs auto-detected, 12 automations. | Developer tools | Stable | Swift | MIT | 0 | |
| OrbIDE Context engine for AI tooling — promote notes into Decisions, Sources, Tasks. MCP server. | Developer tools | Coming soon | TypeScript | MIT | 0 |
Detailed view
Five projects, five jobs.
TaskNebula
StableProductivitySelf-hosted project management with a real AI copilot.
A self-hosted issue tracker that feels like Linear, scales like Jira, and drafts work with you like a pair programmer. Next.js 15 + PostgreSQL 16 + Redis + LiveKit. One curl, three minutes to production.
- Draft-with-AI for backlogs and per-issue assist
- OpenAI + Anthropic + native heuristic planner
- 30+ permission types, 63+ audit-log actions
- Real-time Kanban, sprints, burndown, velocity
- OAuth, signed webhooks, multi-org plans
- Docker Hub: neuraparse/tasknebula
NeuraBar
StableDeveloper toolsYour macOS menu bar, supercharged.
A small, fast, opinionated workspace that lives in the menu bar — tasks, focus, clipboard, notes, automations, and multi-provider AI, one click away. Local-first, no cloud account, plain JSON storage.
- 8 tools in a single popover (⌘1–⌘8)
- ⌘K command palette across tabs
- Auto-detects 11 coding CLIs (Claude Code, Codex, Aider, opencode, Gemini, Amp, Goose, Continue, Plandex, Qwen, Ollama)
- 12 one-click automations with approval gates
- EN / TR localisation, 71 passing tests
- macOS 14+, Swift 5.9, native SMAppService launch-at-login
OrbIDE
Coming soonDeveloper toolsWhere context is built.
Turn your thinking into structured, queryable context that any AI tool can consume. Promote a sentence into a Decision, a paragraph into a Source, a checklist into Tasks — every object becomes addressable from Claude, Cursor, Copilot, or any MCP-compatible agent.
- React 19 + TypeScript 6 + Tauri 2 — ~2 MB native bundle
- Yjs CRDT for offline-first collaboration
- Tiptap rich text + CodeMirror code blocks + LaTeX
- Force-directed 3D knowledge graph (Three.js)
- One-click export: CLAUDE.md, .cursorrules, AGENTS.md, schema/context.json
- MCP server surface — agents query your workspace via standard protocol
- 830+ tests, sub-100 ms cold start
qmesh
Public previewQuantum researchThe quantum substrate of the Neura Parse stack.
One IR across gate, neutral-atom, photonic-CV and pulse modalities. Fault-tolerant promotion is one config flag (surface · BB qLDPC · Gidney–Shutty cultivation). Every run is an ed25519-signed manifest with offline-verifiable hash chains.
- Modality-agnostic IR with deterministic content-hash
- 157 passing tests across phases 1–6
- PyMatching, sliding-window, BP+OSD, neural decoders
- Pasqal Pulser, Strawberry Fields, MrMustard, Bloqade frontends
- QutipEmulator, Aer, Stim, OpenPulse backends
- SLURM / PBS connectors, crash-safe resume via signed lineage
- Compose with Qiskit, Cirq, PennyLane — does not replace them
QMANN
BetaQuantum researchQuantum Memory-Augmented Neural Networks.
Hybrid quantum-classical neural networks with quantum memory operations. Reference implementation for quantum-inspired algorithms suitable for near-term NISQ devices, with three reproducible modes — Theoretical, Simulation, and Hardware.
- Three modes: Theoretical (free), Simulation (free), Hardware (paid)
- Q-Matrix quantum memory layer + Quantum-LSTM controller
- Up to 20 qubits in simulation, 4–12 on real hardware
- Qiskit 2.1+, IBM Quantum Network compatible
- Cost estimator before any paid hardware run
- Apache-2.0, codecov + CI, full docs
Contributing
How to get involved.
Every project lives at github.com/neuraparse. Issues are reviewed weekly by the team that ships the project.
- Bug reports — open an issue on the project repo with a reproduction.
- Feature proposals — start a Discussion before sending a PR; we want the design conversation in public.
- Security disclosures — email security@neuraparse.com, do not file a public issue.
- Research collaboration — qmesh and QMANN are companion repos to peer-reviewed work; reach out for the Collaborator Edition or co-authored studies.
# Try TaskNebula in 30 seconds
$ curl -fsSL https://raw.githubusercontent.com/\
neuraparse/tasknebula/main/scripts/quickstart.sh | bash
# Install NeuraBar (macOS 14+)
$ git clone https://github.com/neuraparse/NeuraBar
$ cd NeuraBar && ./build.sh install
# Run a qmesh example
$ pip install -e ".[all]"
$ python3 examples/dag_cross_modality.py
# Hack on QMANN in simulation mode (free)
$ pip install -e .
$ python examples/02_simulation_mode.py