TaskWing
Health Pass
- License — License: NOASSERTION
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Community trust — 83 GitHub stars
Code Fail
- rm -rf — Recursive force deletion command in install.sh
- rm -rf — Recursive force deletion command in scripts/test_mcp_workspace.sh
Permissions Pass
- Permissions — No dangerous permissions requested
This local-first knowledge layer extracts your project's architecture into a local SQLite database, allowing connected AI tools to quickly query development context via the Model Context Protocol (MCP) without repeatedly reading your entire codebase.
Security Assessment
The tool operates entirely on your local machine and advertises a strict privacy-by-architecture approach, meaning your data stays in local storage rather than syncing to an external cloud. However, the automated rule-based scan flagged the presence of recursive force deletion commands (`rm -rf`) inside `install.sh` and `scripts/test_mcp_workspace.sh`. While this is a common pattern in shell scripts for cleanup, it poses a moderate risk if the paths targeted are ever mishandled or modified maliciously. Additionally, the `curl | sh` installation method inherently executes remote code on your machine. No dangerous OAuth or broad system permissions are requested. Overall risk is rated as Medium.
Quality Assessment
The project is actively maintained, with repository activity as recent as today. It has earned 83 GitHub stars, reflecting a fair level of early community trust. While the README badges display an MIT license, the automated metadata check returned a "NOASSERTION" license status, which creates slight ambiguity regarding its exact open-source legal terms.
Verdict
Use with caution: the local-first privacy design is excellent, but developers should manually review the installation shell scripts for safe `rm -rf` paths before executing them on their systems.
Local-first AI knowledge layer. Extract architecture, query from any AI tool via MCP. Private by architecture.
TaskWing
The local-first knowledge layer for AI development.
Website · Tutorial · Vision · Install
Your AI tools start every session from zero -- and every session, your code context flows through someone else's cloud.
TaskWing takes the opposite approach. One command extracts your architecture into a local knowledge base on your machine. No cloud. No account. Every AI session after that just knows -- without your knowledge base leaving your infrastructure.
Without TaskWing With TaskWing
───────────────── ─────────────
8-12 file reads 1 MCP query
~25,000 tokens ~1,500 tokens
2-3 minutes 42 seconds
No architectural context 170+ knowledge nodes
Install
brew install josephgoksu/tap/taskwing
No signup. No account. Works offline. Everything stays local in SQLite.
Alternative: install via curlcurl -fsSL https://taskwing.app/install.sh | sh
Quick Start
# 1. Extract your architecture (one-time)
cd your-project
taskwing bootstrap
# -> 22 decisions, 12 patterns, 9 constraints extracted
# 2. Connect to your AI tool
taskwing mcp install claude # or: cursor, gemini, codex, copilot, opencode
# 3. Plan and execute with your AI assistant
/taskwing:plan # Create a plan via MCP
/taskwing:next # Get next task with full context
# ...work...
/taskwing:done # Mark complete, advance to next
That's it. Your AI assistant now has local architectural context across every session.
Private by Architecture
TaskWing keeps your knowledge base on your machine. No cloud database, no account, no sync.
YOUR MACHINE EXTERNAL
───────────────────────────────── ─────────────────────────
┌───────────────────────┐
┌──────────────┐ code context │ LLM Provider │
│ Your codebase ├────────────────────>│ (OpenAI, Anthropic, │
└──────────────┘ (bootstrap only) │ Google, Bedrock) │
│ └───────────┬───────────┘
│ │ findings
v │
┌──────────────────────┐ <───────────────────────┘
│ .taskwing/memory.db │
│ Local SQLite │ Your knowledge base.
│ Never uploaded. │ Never leaves your machine.
└──────────┬───────────┘
│ local stdio (MCP)
v
┌──────────────────────┐ ┌───────────────────────┐
│ AI Tool │ may send │ Tool's own cloud │
│ (Claude, Cursor, ├─────────────>│ (per their privacy │
│ Copilot, Gemini) │ to their │ policy) │
└──────────────────────┘ servers └───────────────────────┘
FULL AIR-GAP (everything stays left of the line):
┌──────────────┐ ┌─────────┐ ┌──────────────┐
│ Your codebase ├──────>│ Ollama ├──────>│ .taskwing/ │
└──────────────┘ │ (local) │ │ memory.db │
└─────────┘ └──────┬───────┘
│ local stdio
v
┌──────────────┐
│ Local AI tool │
└──────────────┘
Zero network calls.
What TaskWing controls: Your knowledge base is stored and queried locally. MCP serves responses over local stdio -- no network calls.
What your AI tool controls: Cloud-based tools (Claude, Cursor, Copilot) may send conversations to their own servers. Check their privacy settings (e.g., Cursor's Privacy Mode, Copilot's data retention policies).
Full air-gap: Use Ollama for bootstrap + a local AI tool. Nothing leaves your machine.
Works With
Supported Models
Brand names and logos are trademarks of their respective owners; usage here indicates compatibility, not endorsement.
What It Does
| Capability | Description |
|---|---|
| Local knowledge | Extracts decisions, patterns, and constraints into local SQLite |
| Plan to tasks | Turns a plan into decomposed tasks with architecture context |
| AI-driven lifecycle | Task execution -- next, start, complete, verify |
| Code analysis | Symbol search, call graphs, impact analysis, simplification |
| Root cause first | AI-powered diagnosis before proposing fixes |
| Works everywhere | Exposes everything to 6+ AI tools via local MCP |
Slash Commands
Use these from your AI assistant once connected:
| Command | When to use |
|---|---|
/taskwing:plan |
Clarify a goal and build an approved execution plan |
/taskwing:next |
Start the next approved task with full context |
/taskwing:done |
Complete the current task after verification |
/taskwing:context |
Get full project knowledge dump for complete architectural context |
taskwing mcp install handles this automatically. If you need to configure manually, add to your AI tool's MCP config:
{
"mcpServers": {
"taskwing": {
"command": "taskwing",
"args": ["mcp"]
}
}
}
| Tool | Description |
|---|---|
ask |
Search project knowledge (decisions, patterns, constraints) |
task |
Unified task lifecycle (next, current, start, complete) |
plan |
Plan management (clarify, decompose, expand, generate, finalize, audit) |
code |
Code intelligence (find, search, explain, callers, impact, simplify) |
debug |
Diagnose issues systematically with AI-powered analysis |
remember |
Store knowledge in project memory |
TaskWing integrates with Claude Code's hook system for autonomous plan execution:
taskwing hook session-init # Initialize session tracking
taskwing hook continue-check # Check if should continue to next task
taskwing hook session-end # Cleanup session
taskwing hook status # View current session state
Circuit breakers prevent runaway execution:
--max-tasks=5-- Stop after N tasks for human review--max-minutes=30-- Stop after N minutes
llm:
provider: bedrock
model: anthropic.claude-sonnet-4-5-20250929-v1:0
bedrock:
region: us-east-1
apiKeys:
bedrock: ${BEDROCK_API_KEY}
| Model | Use case |
|---|---|
anthropic.claude-opus-4-6-v1 |
Highest quality reasoning |
anthropic.claude-sonnet-4-5-20250929-v1:0 |
Best default balance |
amazon.nova-premier-v1:0 |
AWS flagship Nova |
amazon.nova-pro-v1:0 |
Strong balance |
meta.llama4-maverick-17b-instruct-v1:0 |
Open-weight general model |
Or configure interactively: taskwing config
taskwing bootstraptaskwing ask "<query>"taskwing tasktaskwing mcptaskwing doctortaskwing configtaskwing start
Documentation
License
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