Farm Table is an open-source task runtime built specifically for AI agents, providing a unified interface for task dependency management and execution tracking.

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106

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Forks

14

Open issues

84

License

Apache-2.0

Last updated

2026-07-27

AI repository intelligence
FR-AI / ANALYSIS

Why it is worth attention

It offers a graph-native task store with dependency tracking, atomic claims, and ready-task detection, with zero infrastructure in embedded mode, and supports multiple backends (GitHub, Jira, Linear) with a normalized schema.

Who it is for

  • AI agent developers
  • DevOps teams building agent workflows
  • Open-source enthusiasts interested in task orchestration
  • Developers using MCP-compatible LLM clients

Use cases

  • Managing complex task dependencies for AI coding agents
  • Coordinating multi-agent workflows with dependency graphs
  • Integrating task management from GitHub, Jira, or Linear into agent pipelines
  • Using MCP tools to let LLMs claim and resolve tasks

Strengths

  • Zero-dependency embedded mode using SQLite, single binary
  • Rich graph queries (critical path, bottlenecks, dependency trees)
  • MCP adapter providing 10 tools for LLM integration
  • Beautiful web dashboard with Kanban, DAG, and inspector

Considerations

  • Early and experimental stage (noted in README)
  • Requires manual setup of Node.js and Go for local development
  • Limited to PostgreSQL for client-server mode (no other databases mentioned)
  • No mention of authentication or multi-tenant support

README quick start

🚜 Farm Table

Farm Table is an open-source task runtime built specifically for AI agents. It provides coding and execution agents with a single, predictable, and robust interface to receive work, understand complex dependency structures, and track execution progress—whether tasks reside in GitHub, Jira, Linear, or Farm Table's own built-in graph-native backend.

When no external platform is connected, the built-in backend provides a graph-native task store complete with dependency tracking, atomic CAS (Compare-And-Swap) claims, and instant ready-task detection. No API keys, no SaaS accounts, and zero complex configuration are required.

NOTE: Farmtable is at an early and experimental stage


🚀 System Architecture & Modes

Farm Table operates transparently in two modes from the exact same codebase:

┌─ Embedded Mode (Default) ──────────────────────────────────────┐
│  ft CLI ──bufconn──► In-Process FarmTableService               │
│                      └──► EntStore (SQLite)                    │
│  Single process. Zero infrastructure. Just works.              │
├─ Client-Server Mode ───────────────────────────────────────────┤
│  ft CLI ──gRPC/TLS──► farmtable-server (Separate Process)      │
│                       └──► EntStore (Postgres)                 │
│  Multi-agent coordination. Production deployments.             │
└────────────────────────────────────────────────────────────────┘
  • Embedded Mode: Automatically selected by default. SQLite is used as the local store at ~/.farmtable/farmtable.db (overridable via FARMTABLE_DB_PATH). Communication is routed through bufconn (an in-memory network connection), creating a single-binary zero-dependency experience.
  • Client-Server Mode: Enabled automatically if the FARMTABLE_SERVER environment variable, --server flag, or the config file server key is supplied. This connects the CLI or agent to a standalone farmtable-server backed by Postgres for multi-agent coordination.

💎 Core Abstractions & Features

📦 Normalized Task Object (NTO)

Every task—whether synced from GitHub or managed locally—is represented in a single, predictable schema defined in Protobuf (proto/farmtable/v1/farmtable.proto).

  • Task State Model: Native tasks use asserted stages such as triage, accepted, working, h

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