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Agent-native issue tracker with convention-based project discovery

Project description

Filigree

Agent-native issue tracker with convention-based project discovery.

CI PyPI Python 3.11+ License: MIT

What Is Filigree?

Filigree is a lightweight, SQLite-backed issue tracker designed for AI coding agents (Claude Code, Codex, etc.) to use as first-class citizens. It exposes 43 MCP tools so agents interact natively, plus a full CLI for humans and background subagents.

Traditional issue trackers are human-first — agents have to scrape CLI output or parse API responses. Filigree flips this: agents read a pre-computed context.md at session start, claim work with optimistic locking, follow enforced workflow state machines, and resume sessions via event streams. For Claude Code, filigree install wires up session hooks and a workflow skill pack so agents get project context automatically.

Filigree is single-project and local-first. No server, no cloud, no accounts. Just a .filigree/ directory (like .git/) containing a SQLite database, configuration, and auto-generated context summary.

Key Features

  • MCP server with 43 tools — agents interact natively without parsing text
  • Full CLI with --json output for background subagents and --actor for audit trails
  • Claude Code integration — session hooks inject project snapshots at startup; bundled skill pack teaches agents workflow patterns
  • Workflow templates — 24 issue types across 9 packs with enforced state machines
  • Dependency graph — blockers, ready-queue, critical path analysis
  • Hierarchical planning — milestone/phase/step hierarchies with automatic unblocking
  • Atomic claiming — optimistic locking prevents double-work in multi-agent scenarios
  • Pre-computed contextcontext.md regenerated on every mutation for instant agent orientation
  • Web dashboard — real-time project overview with filtering and search (optional extra)
  • Minimal dependencies — just Python + SQLite + click (no framework overhead)
  • Session resumptionget_changes --since <timestamp> to catch up after downtime

Quick Start

pip install filigree        # or: uv add filigree
cd my-project
filigree init               # Create .filigree/ directory
filigree install             # Set up MCP, hooks, skills, CLAUDE.md, .gitignore
filigree create "Set up CI pipeline" --type=task --priority=1
filigree ready               # See what's ready to work on
filigree update <id> --status=in_progress
filigree close <id>

Installation

pip install filigree                     # Core CLI
pip install "filigree[mcp]"              # + MCP server
pip install "filigree[dashboard]"        # + Web dashboard
pip install "filigree[all]"              # Everything

Or from source:

git clone https://github.com/tachyon-beep/filigree.git
cd filigree && uv sync

Entry Points

Command Purpose
filigree CLI interface
filigree-mcp MCP server (stdio transport)
filigree-dashboard Web UI (port 8377)

Claude Code Setup

filigree install configures everything in one step. To install individual components:

filigree install --claude-code   # MCP server + CLAUDE.md instructions
filigree install --hooks         # SessionStart hooks (project snapshot + dashboard auto-start)
filigree install --skills        # Workflow skill pack for agents
filigree doctor                  # Verify installation health

The session hook runs filigree session-context at startup, giving the agent a snapshot of in-progress work, ready tasks, and the critical path. The skill pack (filigree-workflow) teaches agents triage patterns, team coordination, and sprint planning via progressive disclosure.

Why Filigree?

Filigree GitHub Issues Jira TODO files
Agent-native (MCP tools) Yes No No No
Works offline / local-first Yes No No Yes
Structured queries & filtering Yes Yes Yes No
Workflow state machines Yes Limited Yes No
Zero configuration Yes No No Yes
Dependency tracking Yes Limited Yes No

Documentation

Document Description
Getting Started 5-minute tutorial: install, init, first issue
CLI Reference All CLI commands with full parameter docs
MCP Server Reference 43 MCP tools for agent-native interaction
Workflow Templates State machines, packs, field schemas, enforcement
Agent Integration Multi-agent patterns, claiming, session resumption
Python API Reference FiligreeDB, Issue, TemplateRegistry for programmatic use
Architecture Source layout, DB schema, design decisions
Examples Runnable scripts: multi-agent, workflows, CLI scripting, planning

Priority Scale

See Workflow Templates — Priority Scale for the full priority definitions (P0–P4).

Development

Requires Python 3.11+. Developed on 3.13.

git clone https://github.com/tachyon-beep/filigree.git
cd filigree
uv sync --group dev

make ci              # ruff check + mypy strict + pytest with 85% coverage gate
make lint            # Ruff check + format check
make format          # Auto-format with ruff
make typecheck       # Mypy strict mode
make test            # Pytest
make test-cov        # Pytest with coverage (fail-under=85%)

Key Conventions

  • Ruff for linting and formatting (line-length=120)
  • Mypy in strict mode
  • Pytest with pytest-asyncio for MCP server tests
  • Coverage threshold at 85%
  • Tests in tests/, source in src/filigree/

Acknowledgements

Filigree was inspired by Steve Yegge's beads project. Filigree builds on the core idea of git-friendly issue tracking, focusing on MCP-native workflows and local-first operation.

License

MIT — Copyright (c) 2026 John Morrissey

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