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MCP Server / AgentCrew

AgentCrew

Chat application with multi-agents system supports multi-models and MCP

★ 189von @saigontechnologyApache-2.0GitHub →

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sse

Tools (3)

Mode

Command

File

Purpose

medium

high

Dokumentation

What is AgentCrew?

AgentCrew lets you build and run a team of specialized AI agents instead of relying on a single generic assistant.

  • Give each agent a role — architect, coder, researcher, reviewer, or browser operator.
  • Agents can hand off work to teammates when a task fits their specialty.
  • Use the same team in a desktop GUI, terminal, automated jobs, or over HTTP.

Watch the demo

Quick Start

1. Install

macOS / Linux

curl -LsSf https://agentcrew.dev/install.sh | bash

Windows

powershell -ExecutionPolicy ByPass -c "irm https://agentcrew.dev/install.ps1 | iex"

pip (any platform)

pip install agentcrew-ai

2. Add an API key

AgentCrew needs at least one AI provider key. Pick your preferred provider and add the key:

Option A — Environment variable

export ANTHROPIC_API_KEY="sk-ant-..."
# or
export OPENAI_API_KEY="sk-proj-..."
# or
export GEMINI_API_KEY="AIza..."

Option B — Config file

mkdir -p ~/.AgentCrew
cat > ~/.AgentCrew/config.json << 'EOF'
{
  "api_keys": {
    "ANTHROPIC_API_KEY": "sk-ant-..."
  }
}
EOF

Option C — Subscription login

If you have a ChatGPT Plus / Pro subscription or a GitHub Copilot subscription, you can log in directly instead of using an API key:

# ChatGPT Plus / Pro (Codex models)
agentcrew chatgpt-auth
agentcrew chat --provider openai_codex

# GitHub Copilot
agentcrew copilot-auth
agentcrew chat --provider github_copilot

Supported providers: Anthropic Claude, OpenAI, Google Gemini, GitHub Copilot, DeepInfra, Together AI, OpenCode, and any OpenAI-compatible endpoint.

Tip: Not sure which provider to pick? Claude and OpenAI work great for most users. See CONFIGURATION.md for provider-specific setup details.

3. Launch AgentCrew

# Desktop GUI
agentcrew chat

# Terminal mode
agentcrew chat --console

On the first launch, AgentCrew will walk you through creating your first agent if you do not already have one.

4. Create your first agent

If you already have an API key set and want to create a new agent from scratch:

agentcrew create-agent

Or define one manually in ~/.AgentCrew/agents.toml:

[[agents]]
name = "CodeAssistant"
description = "Helps write and review code"
tools = ["code_analysis", "file_editing", "web_search", "memory"]
system_prompt = """You are an expert software engineer.
Focus on code quality, security, and maintainability.
Today is {current_date}."""

5. Start working

Switch between agents, attach files, and let your team handle the rest.

/agent Architect
Design a clean API for a task manager.

@Coding
Implement the task manager in Python using FastAPI.

@Reviewer
Review the code for security issues.

Ways to Use AgentCrew

| Mode | Command | Best for | | ----------------- | ----------------------------------------------------------- | ----------------------------------------------------------- | | Desktop GUI | agentcrew chat | Daily interactive work, file drag-and-drop, visual diffs | | Terminal | agentcrew chat --console | Remote servers, low-overhead use, keyboard-driven workflows | | One-shot jobs | agentcrew job --agent "CodeAssistant" "your task" ./files | CI/CD scripts, automation, batch processing | | HTTP API | agentcrew a2a-server | Integrating with other apps, multi-instance setups |

Job mode example:

agentcrew job --agent "CodeAssistant" \
  "Review for security issues" \
  ./src/**/*.py

A2A server example:

agentcrew a2a-server --host 0.0.0.0 --port 41241

What Can Agents Do?

Agents come with a toolkit you enable per agent:

  • Code analysis — understand repo structure, read files, grep, search
  • File editing — write or modify files with search/replace blocks and backups
  • Web search & extraction — pull current information from the web
  • Browser automation — navigate, click, fill forms, and capture screenshots
  • Command execution — run safe shell commands with rate limits and audit logs
  • Memory — remember past conversations and retrieve relevant context
  • Voice — speak and listen using ElevenLabs or DeepInfra (optional)
  • MCP tools — connect to external services via the Model Context Protocol
  • Structured output — enforce JSON schema responses in job mode

Example Agent Configurations

See the examples/agents/ folder for ready-to-use agent setups. To use an example:

cp examples/agents/agents.simple.toml ~/.AgentCrew/agents.toml
agentcrew chat

Configuration Files

AgentCrew stores settings in ~/.AgentCrew/:

| File | Purpose | | ------------------ | ---------------------------------------- | | config.json | API keys, theme, global preferences | | agents.toml | Agent definitions, tools, system prompts | | mcp_servers.json | External tool servers (optional) |

You can edit these files directly or manage them through the GUI settings panel.

Common Console Commands

Inside the chat interface, type:

  • /agent <name> — switch to another agent
  • /clear — start a new conversation
  • /file <path> — attach a file
  • /copy — copy the last response
  • /think <low|medium|high|xhigh> — enable reasoning mode
  • /voice — start voice recording
  • /help - show all available commands
  • exit or quit — close AgentCrew

Next Steps

License

Apache 2.0 License. See LICENSE for details.