pith
AI-native task management for humans & agents. MCP-first, CLI-native, self-hosted. Bring your own model.
Install / Use
claude mcp add SiluPanda -- npx -y github:SiluPanda/pithIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
Data & AnalyticsSupported Platforms
Tags
Our assessment of pith
pith scores 77/100 on our quality scale, 540th of 597 Data & Analytics skills we index.
Its MCP Server is 12 KB long, well organised into 46 sections with 18 code examples: a thorough specification that gives an agent plenty to work with.
It has 10 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated about 7 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
- Our last check on 2026-10-18 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 91/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-10-16. Automated pattern scan on 2026-10-16. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
pith compared with similar skills
All 4 of these similar skills score higher than pith; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| pith (this skill)by SiluPanda | 77 | 10 | 7mo ago | MCP Server |
| Agent-Reachby Panniantong | 100 | 106.6k | 5d ago | CLAUDE.md |
| claude-memby thedotmack | 100 | 105.3k | today | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 78.3k | today | CLAUDE.md |
| CowAgentby zhayujie | 100 | 47.7k | today | CLAUDE.md |
Frequently asked questions
- How do I install pith?
- Run
claude mcp add SiluPanda -- npx -y github:SiluPanda/pith. The install tabs above show the steps for each supported agent. - Which AI agents does pith work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is pith safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 91/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is pith still maintained?
- The repository was last updated about 7 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
Skill content
View source on GitHub<p align="center"> <img src="docs/screenshots/pith-demo.gif" alt="Pith — Board view, list view, task details, and agent activity" width="720"> </p>
AI coding agents do real engineering work — they read specs, write code, fix bugs, and submit PRs. But they're blind to the project's task board. Every context switch requires a human to copy-paste task details, update statuses, and relay decisions.
Pith fixes this. It's an open-source task management system where agents can read tasks, update progress, log work, and create sub-tasks — the same way humans do, but through APIs and MCP instead of a browser.
Quick Start
Docker (recommended)
git clone https://github.com/SiluPanda/pith.git
cd pith/docker
docker compose up
The API is ready at http://localhost:3456. Check it with curl http://localhost:3456/health.
Without Docker
Requires Node.js 20+ and PostgreSQL 16+.
git clone https://github.com/SiluPanda/pith.git
cd pith
cp .env.example .env
# Edit .env — set DATABASE_URL and JWT_SECRET
npm install
npm run db:migrate
npm run dev
Create your first user and project
# Seed sample data (creates admin user, project, and example tasks)
npm run db:seed
# Or use the API directly:
curl -X POST http://localhost:3456/api/v1/users \
-H "Content-Type: application/json" \
-d '{"name": "Admin", "email": "admin@example.com", "role": "admin"}'
# Save the apiKey from the response — it's shown only once
Connect Your AI Agent
Pith is a native MCP tool server. Any MCP-compatible client — Claude Code, Claude Desktop, Cursor, Windsurf, or custom agents — works out of the box.
Setup
Add to your MCP client config (e.g. .mcp.json):
{
"mcpServers": {
"pith": {
"command": "npx",
"args": ["-y", "@pith/mcp-server"],
"env": {
"PITH_URL": "http://localhost:3456",
"PITH_API_KEY": "kb_y…[redacted]"
}
}
}
}
What your agent can do
| Tool | What it does |
|------|-------------|
| list_tasks | Query tasks with filters — status, priority, assignee, labels, free-text search |
| get_task | Get full task details including comments, sub-tasks, and activity history |
| create_task | Create a task with title, description, priority, labels |
| update_task | Change status, priority, assignee, or any other field |
| add_comment | Post a Markdown comment on a task |
| create_subtasks | Break a task into sub-tasks (up to 20 at once) |
| search_tasks | Full-text search across all tasks |
| get_my_tasks | See what's assigned to the current agent |
| get_context | Get rich context — parent task, siblings, recent activity |
| start_session / end_session | Track work sessions with summaries |
Your agent also gets read access to live resources:
pith://project/{slug}/board— Current board state by status columnpith://project/{slug}/backlog— Full backlog with prioritiespith://task/{id}/context— Complete task context for deep workpith://user/{id}/workload— Current assignment load
Example: autonomous coding agent workflow
1. Agent calls get_my_tasks → sees "Fix auth middleware" assigned to it
2. Agent calls get_context → reads task details, parent task, recent comments
3. Agent calls start_session → begins tracked work session
4. Agent writes code, runs tests → (happens outside Pith)
5. Agent calls update_task → moves status to "in_review"
6. Agent calls add_comment → posts summary + PR link
7. Agent calls end_session → records what it accomplished
No human had to copy-paste context or update the board.
CLI
Install globally or use via npx:
npx @pith/cli init --url http://localhost:3456 --key kb_your_key --project my-project
Managing tasks
# List tasks with filters
pith task list --status todo --priority P0
# Create a task
pith task create "Implement rate limiting" --priority P1 --labels security,api
# View task details with comments and activity
pith task show <task-id>
# Update status
pith task update <task-id> --status in_progress
# Add a comment
pith task comment <task-id> "Started work, ETA 2 hours"
# Search across all tasks
pith search "authentication bug"
Agent sessions
pith session start --name "Claude Code" --tasks <task-id-1>,<task-id-2>
# ... do work ...
pith session end <session-id> --summary "Fixed auth bug and added tests"
pith session list
Machine-readable output
Every command supports --json for piping into scripts:
pith task list --status todo --json | jq '.[].title'
Web UI
Pith includes a lightweight web interface at http://localhost:5173 (dev mode) or served by the API in production.
- Board view — Kanban-style columns by status
- List view — Sortable table with filters
- Task detail — Full context with comments, sub-tasks, and activity timeline
- Agent activity feed — Review what your AI agents have been working on
- Session review — Inspect individual agent work sessions
Start the dev server:
cd packages/web
npm run dev
API
Full REST API with OpenAPI/Swagger documentation at /docs (development mode).
Authentication
Every request requires a Bearer token — either an API key or a JWT access token:
# Using an API key
curl -H "Authorization: Bearer kb_your_api_key" http://localhost:3456/api/v1/projects
# Using JWT (get tokens via login)
curl -X POST http://localhost:3456/api/v1/auth/login \
-H "Content-Type: application/json" \
-d '{"email": "admin@example.com", "apiKey": "kb_your_api_key"}'
Key endpoints
| Method | Endpoint | Description |
|--------|----------|-------------|
| GET | /api/v1/projects | List projects |
| POST | /api/v1/projects | Create project (admin) |
| GET | /api/v1/projects/:slug/tasks | List tasks with filters |
| POST | /api/v1/projects/:slug/tasks | Create task |
| GET | /api/v1/tasks/:id | Get task with full context |
| PATCH | /api/v1/tasks/:id | Update task fields |
| POST | /api/v1/tasks/:id/comments | Add comment |
| POST | /api/v1/tasks/:id/subtasks | Batch create sub-tasks |
| GET | /api/v1/search?q=... | Full-text search |
| POST | /api/v1/sessions | Start agent session |
| GET | /api/v1/projects/:slug/analytics | Project analytics |
Full reference: docs/api-reference.md
Roles
| Role | Can do | |------|--------| | admin | Everything — manage users, projects, webhooks, tenants | | member | Create/update tasks, add comments, view projects | | agent | Same as member — designed for AI agent API keys |
Webhooks
Get notified when things happen in your project:
curl -X POST http://localhost:3456/api/v1/projects/my-project/webhooks \
-H "Authorization: Bearer kb_admin_key" \
-H "Content-Type: application/json" \
-d '{"url": "https://your-server.com/webhook", "events": ["task.created", "task.updated"]}'
Events: task.created, task.updated, task.deleted, comment.created, session.started, session.ended, project.created, *
Payloads are signed with HMAC-SHA256 via the X-Pith-Signature header.
Slack & Discord notifications
curl -X POST http://localhost:3456/api/v1/projects/my-project/notifications \
-H "Authorization: Bearer kb_admin_key" \
-H "Content-Type: application/json" \
-d '{"provider": "slack", "name": "dev-channel", "webhookUrl": "https://hooks.slack.com/...", "events": ["task.created", "task.status_changed"]}'
AI Features
AI features are optional. Pith works fully without any AI model configured. When configured, AI enhances — never blocks — your workflow.
Configure a provider
# Via CLI
pith config set ai.provider anthropic
pith config set ai.model claude-sonnet-4-20250514
pith config set ai.apiKey sk-ant-...
# Or via environment variables
export PITH_AI_PROVIDER=anthropic # anthropic, openai, google, groq, ollama
export PITH_AI_MODEL=claude-sonnet-4-20250514
export PITH_AI_API_KEY=sk-ant-...
export PITH_AI_BASE_URL= # optional, for self-hosted models
Supports any provider via Vercel AI SDK: Anthropic, OpenAI, Google, Groq, OpenRouter, and Ollama for local models.
What AI can do
- Decompose tasks — Break a large task into actionable sub-tasks with estimates
- Triage — Auto-suggest priority and labels for new tasks
- Context assembly — Build a briefing document with key points and risks for an agent starting work
- Effort estimation — Suggest time estimates based on historical project data
- Sprint summaries — Generate project summaries from activity data
- Duplicate detection — Flag similar tasks using pg_trgm similarity
# Decompose from CLI
pith task decompose <task-id>
# Get AI-assembled context
pith task context <task-id>
# Via API
curl -X POST http://localhost:3456/api/v1/ai/triage \
-H "Authorization: Bearer kb_..." \
-H "Content-Type: application/json" \
-d '{"title": "Fix memory leak in worker pool", "description": "Workers are not being cleaned up..."}'
Multi-Tenant Mode
Pith supports multi-tenant SaaS deployments with isolated workspaces:
curl -X POST http://localhost:3456/api/v1/tenants \
-H "Authorization: Bearer kb_admin_key" \
-H "Content-Type: application/json" \
-d '{"slug": "acme-corp", "name": "Acme Corp", "plan": "pro"}'
Each tenant gets configurable user and project limits.
Configuration Reference
Environment variables
| Variable | Required | Default | Description |
|----------|----------|---------|-------------|
| DATABASE_URL | Yes (production) | postgres://postgres:postgres@localhost:5432/pith | PostgreSQL connection string |
| JWT_SECRET | Yes (production) | dev fallback | Secret for signing JWT tokens |
| PORT | No | 3456 | API server port |
| HOST | No | 0.0.0.0 | API server bind address |
| CORS_ORIGIN | No | http://localhost:5173 | Allowed CORS origins (comma-separated) |
| LOG_LEVEL | No | info | Log level: debug, info, warn, error |
| PITH_AI_PROVIDER | No | — | AI provider name |
| PITH_AI_MODEL | No | — | AI model identifier |
| PITH_AI_API_KEY | No | — | AI provider API key |
| GITHUB_WEBHOOK_SECRET | No | — | Secret for verifying GitHub webhook signatures |
Project Structure
packages/
core/ Shared types, Zod schemas, constants
db/ PostgreSQL schema, migrations, seed data (Drizzle ORM)
server/ REST API — Fastify, auth, RBAC, webhooks, analytics
ai/ AI integration layer (Vercel AI SDK, provider-agnostic)
mcp-server/ MCP tool server (stdio + HTTP transports)
cli/ Command-line interface (Commander.js)
web/ Web UI (React + Vite)
Contributing
See CONTRIBUTING.md for development setup and guidelines.
git clone h
Truncated for display — read the full file on GitHub.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
