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ClaudeWave

Self-hosted multi-agent collaboration and audit layer for AI-assisted engineering teams

MCP ServersRegistry oficial5 estrellas1 forksPythonApache-2.0Actualizado today
Install in Claude Code / Claude Desktop
Method: UVX (Python) · forkflux
Claude Code CLI
claude mcp add forkflux -- uvx forkflux
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "forkflux": {
      "command": "uvx",
      "args": ["forkflux"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
Casos de uso

Resumen de MCP Servers

# ForkFlux 🐜

**Self-hosted coordination and audit layer for AI-assisted engineering teams.**

ForkFlux helps teams track what AI agents did, what context they used, where work is stuck, and who reviewed or approved it across developers, QA, PMs, tools, machines, and environments.

📚 **Documentation:** [https://docs.forkflux.ai/](https://docs.forkflux.ai/)

> 🎥 **ForkFlux in action**

<img src="https://raw.githubusercontent.com/forkflux/forkflux/main/assets/demo-list.webp" width="49%" /> <img src="https://raw.githubusercontent.com/forkflux/forkflux/main/assets/demo-details.webp" width="49%" />

## Why ForkFlux exists

AI coding agents are becoming part of real engineering workflows. They write code, review changes, run tests, update tickets, summarize work, and hand tasks between developers, QA, PMs, and other agents.

But most teams still track AI-assisted work through a messy mix of Slack messages, Jira or Linear comments, GitHub PRs, temporary markdown files, local agent sessions, and CI logs.

That creates a visibility gap:

- nobody has one timeline of what happened
- agent-generated context gets scattered across tools
- blocked work is easy to miss
- review and approval status is unclear
- QA and developer loops are hard to trace
- AI-generated summaries, artifacts, and decisions are not captured consistently
- teams cannot easily answer "what did the agent do, why, and who checked it?"

ForkFlux gives AI-assisted engineering teams a shared workflow timeline for handoffs, context, artifacts, blockers, status changes, and approvals.

## What ForkFlux is

ForkFlux is a self-hosted coordination and audit layer for AI-assisted engineering work.

It captures structured workflow events from agents and humans, including:

- task handoffs
- context payloads
- changed files, branches, commits, PRs, and other artifacts
- status changes
- blocked and failed work
- review notes
- approval events
- handoff history between roles and teammates

The goal is not to replace Jira, Linear, GitHub, Slack, or your AI coding tools.

ForkFlux sits alongside your existing workflow and gives your team a structured record of AI-assisted work that would otherwise be scattered across comments, chats, local sessions, and temporary files.

# What it is NOT

❌ ForkFlux is not another AI assistant.

❌ ForkFlux is not a local agent framework.

❌ ForkFlux is not shared memory for one developer’s local agents.

❌ ForkFlux is not a replacement for Jira, Linear, GitHub, or Slack.

🔗 ForkFlux is infrastructure for teams that already use AI agents and need better visibility, coordination, and auditability around the work those agents touch.

## How it works

ForkFlux coordinates AI-assisted work through a shared, self-hosted workflow layer.

A typical workflow looks like this:

1. A developer or PM starts a task in their normal workflow.
2. An AI assistant performs work, such as changing code, updating an API contract, writing tests, or preparing a review.
3. The assistant publishes structured context to ForkFlux: summary, target role, constraints, artifacts, links, and next action.
4. Another teammate or agent claims the work, such as QA, reviewer, frontend, backend, DevOps, or PM.
5. ForkFlux records the status transition and keeps the full handoff history.
6. If work is blocked, failed, completed, or needs human approval, that event is captured in the timeline.
7. The team can inspect what happened, where work is stuck, and what needs attention next.

ForkFlux started with agent-to-agent handoffs. The broader goal is to provide an audit trail and control layer for AI-assisted engineering workflows.

## What is included

ForkFlux is a monorepo with two main packages:

| Package | Purpose |
|---|---|
| `forkflux` | Stateful FastAPI coordination service for agents, roles, jobs, events, artifacts, and lifecycle transitions. |
| `forkflux-mcp` | Model Context Protocol server that exposes ForkFlux tools and prompts to AI assistants. |

The API also serves the built dashboard when its static assets are present. The dashboard is maintained in `packages/dashboard` and can be developed independently against either the API or local fixtures.

The MCP server exposes agent-facing tools for creating jobs, listing available work, claiming tasks, updating status, and fetching job details.

ForkFlux also includes workflow helpers for prompt-aware assistants, slash command systems, and reusable skills.

## Quick start

Run the local demo setup:

```bash
uvx --from forkflux forkflux quickstart
```

Start the API server:

```bash
uvx --from forkflux forkflux serve
```

The quickstart creates example roles and agents, installs supported workflow helpers, and registers the MCP server with supported local assistant CLIs.

The automated quickstart requires at least two of these CLIs to already be installed: Codex, Claude Code, OpenCode, or Hermes. For a single-client or production-like setup, use the [manual setup guide](https://docs.forkflux.ai/manual-setup) instead.

For complete setup instructions, see the [Quickstart](https://docs.forkflux.ai/quickstart).

## Who ForkFlux is for

ForkFlux is for engineering teams that already use AI coding agents in real work and need better coordination across people, tools, and environments.

It is especially useful for teams that have:

- multiple developers using local or isolated AI assistants
- QA, review, PM, frontend, backend, or DevOps handoffs
- self-hosting or security requirements
- AI-generated work moving through GitHub, Jira, Linear, Slack, or CI
- a need to understand where AI-assisted work is blocked, reviewed, or approved

## Community and contributing

Our goal is to make ForkFlux the standard job exchange protocol for AI-native engineering teams.

- 💬 Join Discord: [https://discord.gg/wTJVctJwn3](https://discord.gg/wTJVctJwn3)
- 🛠 Contribute: see the [Contributing guide](https://docs.forkflux.ai/contributing)
- 🐛 Report issues: [https://github.com/forkflux/forkflux/issues](https://github.com/forkflux/forkflux/issues)

## License

ForkFlux is licensed under Apache-2.0. See [LICENSE](LICENSE) for the full license text.
agentic-workflowai-agentsaudit-trailcoordination-buscross-devicedeveloper-productivityinfrastructureloggingmcpmodel-context-protocolorchestrationtask-delegation

Lo que la gente pregunta sobre forkflux

¿Qué es forkflux/forkflux?

+

forkflux/forkflux es mcp servers para el ecosistema de Claude AI. Self-hosted multi-agent collaboration and audit layer for AI-assisted engineering teams Tiene 5 estrellas en GitHub y se actualizó por última vez today.

¿Cómo se instala forkflux?

+

Puedes instalar forkflux clonando el repositorio (https://github.com/forkflux/forkflux) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar forkflux/forkflux?

+

forkflux/forkflux aún no ha sido auditado por nuestro agente de seguridad. Revisa el repositorio original en GitHub antes de usarlo en producción.

¿Quién mantiene forkflux/forkflux?

+

forkflux/forkflux es mantenido por forkflux. La última actividad registrada en GitHub es de today, con 0 issues abiertos.

¿Hay alternativas a forkflux?

+

Sí. En ClaudeWave puedes explorar mcp servers similares en /categories/mcp, ordenados por popularidad o actividad reciente.

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