- Explore MCP Servers
- AgentCrew
Agentcrew
What is Agentcrew
AgentCrew is a sophisticated chat application that utilizes a multi-agent system to enhance interactive AI experiences. It supports multiple models and integrates various features such as intelligent transfers and file integration.
Use cases
Use cases for AgentCrew include automated customer service agents, educational tutoring systems, collaborative project management tools, and interactive entertainment applications.
How to use
To use AgentCrew, clone the repository, install the necessary packages, and set up your API keys for the desired models. Start an interactive chat by running ‘agentcrew chat’ in your terminal.
Key features
Key features of AgentCrew include a multi-agent architecture, support for multiple LLM providers, intelligent transfer capabilities, file integration, web search functionalities, and a modular extension system.
Where to use
AgentCrew can be used in various fields such as customer support, educational tools, collaborative work environments, and any application requiring advanced interactive AI communication.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Agentcrew
AgentCrew is a sophisticated chat application that utilizes a multi-agent system to enhance interactive AI experiences. It supports multiple models and integrates various features such as intelligent transfers and file integration.
Use cases
Use cases for AgentCrew include automated customer service agents, educational tutoring systems, collaborative project management tools, and interactive entertainment applications.
How to use
To use AgentCrew, clone the repository, install the necessary packages, and set up your API keys for the desired models. Start an interactive chat by running ‘agentcrew chat’ in your terminal.
Key features
Key features of AgentCrew include a multi-agent architecture, support for multiple LLM providers, intelligent transfer capabilities, file integration, web search functionalities, and a modular extension system.
Where to use
AgentCrew can be used in various fields such as customer support, educational tools, collaborative work environments, and any application requiring advanced interactive AI communication.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
AgentCrew: Your Multi-Agent AI Assistant Framework
Introduction
What is AgentCrew?
AgentCrew helps you build AI assistants. You can create a team of AI “agents.”
Each agent focuses on a specific area. These agents work together to complete
tasks. This teamwork can produce good results.
Who Might Like AgentCrew?
AgentCrew is for anyone interested in AI assistants. If you want to see how
different AIs can team up, or if you want to build your own AI helpers,
AgentCrew can help.
Key Benefits
- Solves Complex Problems: Use an AI team for tasks too big for one AI.
- Works with Many AI Models: Supports AI from OpenAI (GPT), Anthropic
(Claude), Google (Gemini), GitHub Copilot, and others. Switching models is
simple. - Creates Expert Agents: Make AI agents for specific jobs, like writing or
research. - Connects to Other Tools: Agents can use external software through the
Model Context Protocol (MCP). - User Control: You can approve or deny when an agent wants to use a tool.
- Simple to Use: Chat with your AI agents using a text display or a
graphical window. - Manages Conversations: Easily go back to earlier messages or combine
messages.
Short Demo
https://github.com/user-attachments/assets/f0d8d2a2-a163-446d-9536-45e54e6bde37
💡 Core Ideas Behind AgentCrew
AgentCrew uses these main ideas:
-
AI Teamwork: Just like a human team. Each person has a special skill.
Projects work when these specialists help each other. AgentCrew applies this
idea to AI. You create different AI agents. Each has its own instructions and
tools. For example, one agent might find information online. Another might
write summaries. -
Smart Task Sharing: Agents in AgentCrew can decide to pass tasks to
another agent. They have instructions on when and how to share work and
information. This lets the right AI take over at the right time. -
Flexible AI Models Selection: AgentCrew lets you use different AI models
(Large Language Models like GPT or Claude). You are not stuck with one AI
provider. AgentCrew makes it easy to connect and use the AI model you choose.
✨ Key Features
Here are some things AgentCrew can do:
🤖 Wide AI Model Support:
- Works with AI from Anthropic (Claude series), Google (Gemini series), OpenAI
(GPT series), Groq, and DeepInfra. - Supports GitHub Copilot. Set up authentication with
agentcrew copilot-auth. - Connect to custom AI providers compatible with OpenAI.
🚀 Strong Agent Capabilities:
- Define multiple AI agents, each with its own expertise.
- Agents can pass tasks to other agents when they need to.
- Customize each agent’s system prompt. You can include information like the
current date.
🔄 Adaptive Behaviors for Agents:
- Use the
adapttool to declare rules in a"when...do..."format. For
example,
when user asks for code examples, do provide complete annotated snippets. - Agents automatically store and apply these behaviors to keep improving
interactions. - Manage and update adaptive rules at any time for fine-tuned personalization.
🛠️ Powerful Tools for Agents with User Control:
- Tool Call Approval: You decide if an agent can use a tool. AgentCrew will
ask for your permission before a tool is run. This gives you more control. - Model Context Protocol (MCP): Lets agents connect to external tools like
Jira. - Web Search: Agents can find current information online.
- Clipboard Access: Agents can copy text from your clipboard or write text
to it. - Memory: Agents remember past parts of your conversation. This helps them
give relevant replies. You can tell agents to forget certain topics. - Code Assistance: Agents can analyze code and help with coding tasks.
💬 Easy Interaction and Chat Management:
- Dual Interfaces: Chat with AgentCrew using a text console or a graphical
window (GUI). - File Handling: AI agents can work with text and image files in chat.
AgentCrew also supports PDF, DOCX, XLSX, and PPTX files. - Streaming Responses: Get real-time replies from AI agents.
- “Thinking Mode”: Some AI models can show their reasoning process.
- Rollback Messages: Easily go back to an earlier point in your
conversation. - Consolidate Messages: Combine multiple chat messages into one using the
/consolidatecommand.
⚙️ Simple Configuration:
- Set up AgentCrew using text files or, more easily, through its graphical
user interface (GUI). - The GUI helps you manage API keys, agent settings, and MCP server connections.
- Save and load your conversation histories.
✅ Prerequisites
- Python 3.12 or newer.
uv(a fast Python package manager). Install it withpip install uv.- Git (a system for managing code versions).
- API keys for the AI models you plan to use. You need at least one API key.
📦 Installation
You can install AgentCrew using a quick script or by following standard steps.
Quick Install (Linux and MacOS):
curl -LsSf https://agentcrew.dev/install.sh | bash
Quick Install (Windows):
powershell -ExecutionPolicy ByPass -c "irm https://agentcrew.dev/install.ps1 | iex"
Standard Installation (Good for all computers):
-
Get the code:
git clone https://github.com/saigontechnology/AgentCrew.git cd AgentCrew -
Set up a Python environment:
uv sync uv run AgentCrew/main.py chat -
Install AgentCrew:
uv tool install .
▶️ Getting Started / Basic Usage
Chat with AgentCrew using its interface. The graphical interface (GUI) is
usually the easiest way to start.
Using the command line:
To start AgentCrew, open your terminal and use the agentcrew chat command.
Here are some common ways to use it (assuming you have installed AgentCrew using
the steps above):
-
Start with the GUI (default):
agentcrew chat -
Start with the console interface:
agentcrew chat --console -
Choose a specific AI provider (e.g., OpenAI) for the main chat:
agentcrew chat --provider openai --console(Replace
openaiwithclaude,groq,google,deepinfra, or
github_copilotas needed.) -
Specify a custom agent configuration file:
agentcrew chat --agent-config /path/to/your/agents.toml -
Specify a custom MCP servers configuration file:
agentcrew chat --mcp-config /path/to/your/mcp_servers.json -
Choose a specific AI model for memory processing:
agentcrew chat --memory-llm claude --console(This sets which AI model helps the system analyze and manage conversation
memory. Replaceclaudewithopenai,groq,google,deepinfra, or
github_copilot.) -
Combine options:
agentcrew chat --provider google --memory-llm openai --agent-config custom_agents.toml --console
Remember to replace /path/to/your/agents.toml and
/path/to/your/mcp_servers.json with the actual paths to your configuration
files if you use those options.
To set up GitHub Copilot authentication: Before using GitHub Copilot as a
provider, run:
agentcrew copilot-auth
In-Chat Commands (for console and GUI):
/clearorCtrl+L: Starts a new chat./copyorCtrl+Shift+C: Copies the AI’s last reply./file <path/to/file>: Adds a file’s content to your message./agent [agent_name]: Switches to a different AI agent./consolidate <num_of_preserve_messages>: Combines selected messages into
one./think <level>: Turns on “thinking mode” for some AIs. Example:
/think medium. Use/think 0to turn it off.exitorquit: Closes the chat.
🔧 Configuration Overview
AgentCrew needs API keys for AI models. You also define your AI agents. The
easiest way to configure AgentCrew is through its graphical user interface
(GUI).
- API Keys: Needed for services like OpenAI or GitHub Copilot. Manage these
in the GUI (Settings -> Global Settings) or set them as environment variables. - Agent Definitions: Describe your agents (name, skills, tools) in the GUI
(Settings -> Agents). This edits theagents.tomlfile, usually in
~/.AgentCrew/agents.toml. - Global Settings & MCP Servers: Manage other settings and Model Context
Protocol server connections using the GUI. This updates files like
~/.AgentCrew/config.jsonand~/.AgentCrew/mcp_servers.json.
For full configuration details, see CONFIGURATION.md (this file will contain
detailed setup information).
👨💻 Development & Customization
If you are a developer, you can add to AgentCrew:
- New Tools: Create new tool modules in the
AgentCrew/modules/folder. - New AI Providers: Add support for more AI services. For OpenAI-compatible
ones, add them through the GUI or by editingconfig.json. - Custom Agents: Edit agent settings using the GUI or directly in the
agents.tomlfile. - Share Example Agents: You can create useful agent configurations and share
them with the community by adding them to theexamples/agents/folder in the
project.
⚠️ Security and Responsible Usage Advisory ⚠️
You control how AgentCrew and its AI agents work. You are responsible for:
- The instructions you give your AI agents.
- The tools you let agents use. The Tool Call Approval feature helps you
manage this. - Any results from your prompts or tool setups. This includes risks like data
leaks or unintended actions.
Please review all prompts and tool settings.
- Give agents only the permissions they truly need.
- Do not put secret information (like passwords or API keys) directly in agent
prompts. - Be very careful with tools that can access many files or the internet, even
with approval.
AgentCrew is powerful. Please use it responsibly.
🤝 Contributing
We welcome contributions. Feel free to submit pull requests or open issues for
bugs, new ideas, or improvements.
📜 License
AgentCrew is available under the Apache 2.0 License.
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










