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Agent-native issue tracker with convention-based project discovery

Project description

Filigree

Local-first issue tracker designed for AI coding agents — SQLite, MCP tools, no cloud, no accounts.

CI PyPI Python 3.11+ License: MIT

Filigree Dashboard

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 53 MCP tools so agents interact natively, plus a full CLI for humans and background subagents.

Traditional issue trackers are human-first — agents scrape CLI output or parse API responses. Filigree flips this: agents get a pre-computed context.md at session start, claim work with optimistic locking, and resume sessions via event streams without re-reading history. For Claude Code, filigree install wires up session hooks and a workflow skill pack so agents get project context automatically.

Filigree is local-first. No cloud, no accounts. Each project gets a .filigree/ directory (like .git/) containing a SQLite database, configuration, and auto-generated context summary. Installations support two modes: ethereal (default, per-project) and server (persistent multi-project daemon).

Key Features

  • MCP server with 53 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 Kanban drag-and-drop, Graph v2 dependency exploration, Files/Health views, and optional multi-project server mode
  • 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 step by step.

Why Filigree?

Filigree is designed for a specific niche: local-first, agent-driven development. It is not a replacement for GitHub Issues or Jira.

Feature Filigree GitHub Issues Jira
Agent-native MCP tools Yes No No
Works offline, no account needed Yes No No
Enforced workflow state machines Yes Limited Yes
Dependency graph + critical path Yes Limited Yes
Structured queries and filtering Yes Yes Yes
Multi-user cloud collaboration No Yes Yes
Integration ecosystem (CI, Slack) No Yes Yes

When NOT to Use Filigree

Filigree is designed for one niche well. It is the wrong tool if you need:

Team collaboration across machines. Filigree has no cloud sync, no accounts, and no network-accessible API beyond localhost. If your team of humans needs to file bugs, assign tickets, and comment across different machines, use GitHub Issues, Linear, or Jira.

Integration with your existing toolchain. Filigree does not connect to CI pipelines, Slack, PagerDuty, or third-party services. If your workflow requires automated ticket creation from alerts or Slack-based triage, Filigree will not fit without custom scripting.

A persistent project record outlasting the repository. Your .filigree/ directory lives with your project. If you need an audit trail that survives repository deletion or is accessible after the project ends, use a hosted service.

Multi-project portfolio management. The web dashboard supports switching between local projects, but Filigree has no cross-project reporting, resource allocation, or roadmap views. It tracks tasks, not portfolios.

Mobile or browser-based access. The dashboard runs on localhost. If stakeholders need to read or file issues from their phone or a machine where the project is not checked out, Filigree is not the right choice.

The sweet spot: one developer or agent team, one project, offline or airgapped, where you want structured workflow enforcement and agent-native tooling without standing up external infrastructure.

Documentation

Document Description
Getting Started 5-minute tutorial: install, init, first issue
CLI Reference All CLI commands with full parameter docs
MCP Server Reference 53 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

Priority Label Meaning
P0 Critical Drop everything
P1 High Do next
P2 Medium Default
P3 Low When possible
P4 Backlog Future consideration

Full definitions: Workflow Templates — Priority Scale

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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