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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
brew install josephgoksu/tap/taskwingNo signup. No account. Works offline. Everything stays local in SQLite.
Alternative: install via curl
curl -fsSL https://taskwing.app/install.sh | sh# 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. Set a goal and go
taskwing goal "Add Stripe billing"
# -> Plan decomposed into 5 executable tasks
# 4. Execute with your AI assistant
/taskwing:next # Get next task with full context
# ...work...
/taskwing:done # Mark complete, advance to nextThat's it. Your AI assistant now has local architectural context across every session.
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.
Brand names and logos are trademarks of their respective owners; usage here indicates compatibility, not endorsement.
| Capability | Description |
|---|---|
| Local knowledge | Extracts decisions, patterns, and constraints into local SQLite |
| Goal to tasks | Turns a goal into an executable plan with decomposed tasks |
| 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 |
Use these from your AI assistant once connected:
| Command | When to use |
|---|---|
/taskwing:ask |
Search project knowledge (decisions, patterns, constraints) |
/taskwing:remember |
Persist a decision, pattern, or insight to project memory |
/taskwing:next |
Start the next approved task with full context |
/taskwing:done |
Complete the current task after verification |
/taskwing:status |
Check current task progress and acceptance criteria |
/taskwing:plan |
Clarify a goal and build an approved execution plan |
/taskwing:debug |
Root-cause-first debugging before proposing fixes |
/taskwing:explain |
Deep explanation of a code symbol and its call graph |
/taskwing:simplify |
Simplify code while preserving behavior |
MCP setup (manual)
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 |
Autonomous task execution (hooks)
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 stateCircuit breakers prevent runaway execution:
--max-tasks=5-- Stop after N tasks for human review--max-minutes=30-- Stop after N minutes
AWS Bedrock setup
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 goal "<goal>"taskwing ask "<query>"taskwing tasktaskwing plan statustaskwing slashtaskwing mcptaskwing doctortaskwing configtaskwing start
