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ScriptsMay 12, 2026·2 min de lecture

Hive Framework — Outcome-Driven Multi-Agent Harness

Hive Framework turns natural-language goals into generated agent graphs and dashboards, giving teams a production-minded multi-agent harness.

Introduction

Hive Framework turns natural-language goals into generated agent graphs and dashboards, giving teams a production-minded multi-agent harness.

  • Best for: teams that want graph generation, dashboards, and MCP-connected business workflows in one harness
  • Works with: Python 3.11+, uv workspaces, browser dashboard, LiteLLM-compatible providers, MCP tool integrations
  • Setup time: 20-40 minutes

Practical Notes

  • Quant: the repo advertises 102 MCP tools and a uv workspace split across core runtime and tool environments.
  • Quant: the quickstart provisions at least two virtual environments (core/.venv and tools/.venv) plus encrypted credentials.

Rollout pattern

  • Use the quickstart script exactly as documented and avoid improvising the install path on first run.
  • Pilot one outcome-driven workflow that touches a single external system before you let Hive generate broader graphs.
  • Treat the browser dashboard as an audit surface: capture screenshots or logs from the first few generated runs.

Watchouts

Because Hive generates orchestration structures for you, the main risk is over-trusting generated graphs before you understand the tool permissions and business-system side effects.

FAQ

Q: Can I install it with pip editable mode? A: No. The README warns that the project uses a uv workspace layout and that pip install -e . will not work correctly.

Q: What makes it different from a basic agent SDK? A: It includes graph generation, dashboarding, credential handling, and MCP-oriented system integration.

Q: What is the first validation step? A: Run the quickstart, open the dashboard, and execute one sample agent with limited scope.

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Source et remerciements

Source: https://github.com/aden-hive/hive > License: Apache-2.0 > GitHub stars: 10,302 · forks: 5,647

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