Tools tagged with "Multi-agent workflows"

jcode is a terminal AI coding assistant for developers who want to choose their model provider and carry useful context between conversations. It supports local and self-hosted model endpoints alongside cloud services.

SWE AF is an AI coding agent system built on AgentField for developers delegating changes across a repository or several related codebases. It divides work among agents and adjusts the remaining plan when tasks run into problems.

Agent of Empires is a self-hosted session manager for developers working with several AI coding agents in parallel. It lets you follow work across projects and branches without keeping every agent's terminal open.

HyperResearch is a research agent for Claude Code and OpenAI Codex that produces cited reports and keeps sources for later questions. It's for researchers who want to review the evidence behind a report and reuse their collected material.

Contrabass coordinates AI coding agents working through project issues, for developers managing several tasks or agent teams. It runs locally on macOS and Linux and reimplements OpenAI's Symphony approach.

Albert coordinates Claude Code agents for developers who want to hand off a coding goal that spans several tasks. It plans the work and continues through successive rounds until it reaches the goal or a requested review checkpoint.

Hermes Browser Extension puts an existing Hermes Agent in a browser side panel for people who want to ask about the pages they're reading. Page context works through local or remote API connections; Hermes Cloud and dashboard-ticket connections are chat-only.

Agency Orchestrator coordinates specialist AI roles for developers and solo builders working on product plans, research or content. A task description can become a team that divides the work and combines its results.

Fable Orchestrator is a local routing skill for developers who want separate planning and implementation roles in Codex. Claude Fable makes planning decisions and reviews results, while Codex retains control of the workspace and tools.

Claw Orchestrator gives developers one interface for multiple coding agents and checks their results independently. You define acceptance criteria, and the runtime executes the checks and keeps the evidence on disk.

AgentsMesh coordinates AI coding agents across local machines and servers for developers managing concurrent work. A shared console lets teams assign tasks, watch terminals and follow progress across agents.

Codewhale is a coding assistant for developers who want an agent to inspect projects, make changes and check the results. It runs on your computer and lets you choose the model and the permissions it works under.

DevSpace is a self-hosted MCP server for developers who want ChatGPT, Claude or another compatible client to work in projects on their own machine. It connects an assistant to selected local folders and the project's terminal tools.

Remembra Relay saves coding session handoffs so developers can switch assistants or resume a project on another machine without reconstructing its progress. The next agent receives a brief of completed work, unfinished tasks and failing checks.

Agentlas OS is an open-source AI agent framework for projects that need specialist teams and shared project context. It runs on macOS, Windows and Linux, with local document indexing, semantic search and memory retrieval. You supply the model. Using a cloud model sends requests to that provider and may incur charges.

AgileRL is an open-source Python framework for teams training AI agents on their own tasks, including LLM agents and agents for robotics, finance or logistics. Its evolutionary hyperparameter tuning adjusts training settings during a run, reducing the need for separate tuning trials. The framework uses the Apache 2.0 license.

LocalAI is a self-hosted AI runtime for developers and teams that want to run models on their own hardware. It brings language, speech, vision and media generation into one server that existing AI applications can connect to.

Kady is an AI research assistant for scientists who want to turn plain-language requests into analyses, literature reviews and research outputs. It works in a desktop workspace where you can inspect its code and files, redirect ongoing work or stop a run.

Bisheng is a self-hosted AI application platform for teams working with business documents and processes. It supports tasks such as document review, support ticket assistance and fixed-layout report generation, including workflows that need human judgment during execution.

KADATH is a self-hosted AI agent runtime for developers and researchers comparing agents against a measurable goal. It runs successive generations of agents and selects stronger approaches, but model calls require OpenAI's cloud API, an API key and internet access.

ChatML is a desktop workspace for developers running several Claude Code tasks at once. It brings agent activity and code changes into one view so you can review work before merging it.

Mastra is a TypeScript framework for developers building self-hosted AI agents and applications with local models through LM Studio. It supports gpt-oss, Qwen3 and DeepSeek through an OpenAI-compatible model server. The framework can also call OpenAI, Anthropic and Gemini, which send model requests to those remote providers.

DarkMoon runs autonomous penetration tests for security teams, DevSecOps engineers and red teamers. It discovers a target's technology stack, assigns specialist AI agents and tests vulnerabilities across connected systems.

Ellama is an AI assistant for Emacs users who want help with writing and code inside their editor. It handles requests about selected text as well as longer conversations and coding tasks that need several steps.

Jean is a desktop and self-hosted workspace for developers running coding agents across multiple projects. Repositories, terminals and git operations run on your computer or server, while the connected agents use your own subscriptions or API access. With Claude Code’s standard cloud connection, prompts and model responses go to its remote provider.

Shinkai lets people build AI agents to automate tasks without writing code. Its desktop app can run agents entirely offline with local models, including workflows that handle sensitive data.

fx is a coding agent for developers who prefer working in a terminal and researchers who want to embed an agent in their own software. Its shell-style interface keeps tool activity alongside the conversation and preserves terminal scrollback.

Claude Command Center helps developers keep track of coding agents working across multiple projects. It finds sessions launched in a terminal as well as through the dashboard, and agents keep running when you close it.

VoltAgent is a TypeScript AI agent framework for developers building assistants and automated workflows with local models through Ollama. Its VoltOps console can be self-hosted or used as a cloud service. Model execution depends on the provider: Ollama supports local inference, while OpenAI, Anthropic and Google connections send requests to those remote services.

WhipCode is an open-source coding agent for developers tackling jobs that exceed a single model context window. It lets agents divide the work while you follow their progress and send further instructions.

Agent Pilot is a desktop AI workflow builder for people who want to combine model conversations with tools and code. It runs on Windows, Linux and Intel Macs and is open source under AGPL-3.0. You can chat with one model or build a graph of cooperating agents, with human input included where a task needs it.

Devo is a coding agent for developers who want to choose their model provider and run the agent on their own machine. Its desktop app and terminal interface handle coding and other engineering tasks that require multiple steps.

Clippinator is a Python AI coding assistant that runs on your machine while its agents use GPT-4 through OpenAI's cloud API. It's for developers who want to delegate project work and review the results as it proceeds. It requires an OpenAI API key and internet access, so model processing happens in the cloud rather than on your hardware.

OpenCodeReview is a locally installed AI code review CLI for developers who want findings tied to specific code lines. It sends code to a configured LLM endpoint through OpenAI- or Anthropic-compatible APIs. The local CLI handles the review process; model inference depends on that endpoint.