# massgen/MassGen

🚀 MassGen is an open-source multi-agent scaling system that runs in your terminal, autonomously orchestrating frontier models and agents to collaborate, reason, and produce high-quality results. | Join us on Discord: discord.massgen.ai

Repository: https://github.com/massgen/MassGen
Canonical: https://ross.abutalabs.com/products/massgen
Homepage: https://docs.massgen.ai
Language: Python
License: NOASSERTION
License Family: other
Topics: agent, llm, multi-agent, test-time-scaling, agentic-ai, autonomous-agents, cli, collaborative-ai, conversational-ai, genai, generative-ai, llm-orchestration, model-context-protocol, python, terminal-ui, tool-calling
Last push: 2026-06-12T18:38:37+00:00

## Health v2 (maintenance only)
Score: 72/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 87, release rhythm 76, longevity 29
- inputs: {"age_days": 411, "days_push": 82, "days_rel": 82, "gap_med": 2, "n_releases_24m": 128}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1122, forks 175 (observed 2026-08-28T04:03:40.154556+00:00)

## What it is
MassGen is an open-source multi-agent scaling system that runs in the terminal, orchestrating multiple frontier LLM agents to work on the same task in parallel. Agents observe, critique, and build on each other's work, then vote to select the best collectively validated answer.

## Use cases
- orchestrate multiple llm agents to collaborate on a complex task
- improve answer quality through multi-agent consensus and voting
- run autonomous ai agents from the terminal
- scale test-time compute with parallel agent refinement
- coordinate agents that use tools and mcp servers
- compare and validate outputs from frontier models automatically

## When to choose
- you want redundant parallel agent attempts with collective validation rather than a single agent run
- you need a terminal-first, pip-installable multi-agent orchestrator supporting multiple LLM backends
- your task benefits from iterative critique and consensus, like research, coding, or analysis

## When to avoid
- you need a lightweight single-agent pipeline where multi-agent overhead and token cost are wasteful
- you require a GUI or hosted web interface rather than a terminal tool
- you need strict latency or cost budgets, since parallel agents multiply inference spend

## Facets
- artifact type: cli-tool
- maturity: active
- function: agent-framework, llm-inference, cli, terminal-ui, mcp
- domain: artificial-intelligence, large-language-models, developer-tools
- platform: python, cli, cross-platform
- tags: multi-agent, test-time-scaling, llm-orchestration, collaborative-ai, consensus-voting, tool-calling, ai-agents, command-line

## Member repositories
- massgen/MassGen (main) score 72

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:40.154556+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:40:56.629884+00:00, confidence not recorded.
  - readme: https://github.com/massgen/MassGen (fetched 2026-08-28T04:03:40.154556+00:00, sha 24c394b46957)
- Data as of 2026-08-30T08:39:29.467469+00:00.