1. Conduid
  2. AI
  3. Agentcrew
MCP server · AI

Agentcrew

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

83Excellent

Scored 6 hours ago · breakdown

About Agentcrew

Agentcrew is an MCP server published by saigontechnology in the AI category: chat application with multi-agents system supports multi-models and MCP.

The repository has 219 stars and 43 forks, with the last commit yesterday. Recent commit activity is the strongest signal that reported issues will get attention.

Install

From source
git clone https://github.com/saigontechnology/AgentCrew

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (11)

adaptive_learningLearn behavioral patterns from interactions

Parameters not published.

browserFull browser automation (navigate, click, form fill)

Parameters not published.

clipboardRead/write system clipboard

Parameters not published.

code_analysisRead files, grep, analyze repo structure

Parameters not published.

command_executionRun shell commands (rate limits, audit logs)

Parameters not published.

fetch_webpageExtract content from a URL

Parameters not published.

file_editingWrite/modify files (search-replace blocks, backups)

Parameters not published.

memoryStore and retrieve conversation context

Parameters not published.

transferHand off tasks to other agents

Parameters not published.

voiceSpeak and listen (ElevenLabs or DeepInfra)

Parameters not published.

web_searchSearch the web via Tavily

Parameters not published.

Ask AI

✦

Ask AI about Agentcrew

Powered by Claude · Grounded in docs

I know everything about Agentcrew. Ask me about installation, configuration, usage, or troubleshooting.

Security checks

Static checks derived from the repository 6 hours ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • ✓License declaredUsable under a stated license.
  • ✓Tests presentA test suite exists in the repository.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • !No dynamic code executionSource scan found eval or shell execution. Review how tool inputs reach it before granting credentials.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

v0.22.0v0.22.0 · 16 Oct 2026AgentCrew 0.22.0 Released October 16, 2026 This release adds richer delegation workflows, safer cancellation, Git worktree tools, and request-scoped YOLO approvals. Highlights Delegates can ask the source agent for clarification.**…
v0.21.5v0.21.5 · 2 Oct 2026This release improves console input handling and visual-mode selection, adds new model options, and updates OpenAI Responses API support. Highlights Improved console input lifecycle:** `/list` and `/visual` now check that chat input has…
v0.21.4v0.21.4 · 24 Sep 2026AgentCrew 0.21.4 This release improves reasoning continuity across turns, adds background summaries for long tool results, and refreshes provider and model support. Highlights Preserve OpenAI Responses reasoning across turns.** Encrypted…
v0.21.3v0.21.3 · 3 Sep 2026🚀 What's Changed ✨ New Features Updated CommandCode & CrofAI model catalogs** ([`41ad2039`](https://github.com/daltonnyx/AgentCrew/commit/41ad2039)) New models added:** `GLM-5.3 Flash` & `GLM-5.3` (Z.ai) — CommandCode `MiniMax M3 (Free)` &…
v0.21.2v0.21.2 · 26 Aug 2026🐛 Bug Fixes fix(core): suppressed the athrow error** ([`a1111516`](https://github.com/daltonnyx/swissknife/commit/a1111516)) Suppressed the `generator didn't stop after athrow()` `RuntimeError` that could surface during HTTP/transport…

README


Why AgentCrew?

AgentCrew lets you build a team of specialists, each with the right tools and personality for the job.

  • An Architect that weighs trade-offs before a line of code is written.
  • A Coder that implements cleanly — no scope creep, no over-engineering.
  • A Reviewer that catches what others miss.
  • A Researcher that cross-references multiple sources before drawing conclusions.
  • A Browser Operator that navigates web apps, fills forms, and clicks through workflows.

Agents hand off work to each other when a task needs a different specialty. You stay in control, orchestrating the team from one interface.

When AgentCrew fits: You have a complex task that benefits from multiple perspectives — building a feature from design to deployment, researching and writing a report, or automating a multi-step workflow.

When a single assistant is enough: You need one focused conversation with no tool access or multi-agent orchestration.


Quick Start

1. Install (10 seconds)

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 — or skip this step entirely

Most tools need a paid API key. AgentCrew supports several options that don't require one:

Subscription-based (no API key needed):

# OpenCode Go — curated open-source models (GLM, Kimi, MiMo, Qwen)
agentcrew chat --provider opencode_go

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

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

Pay-as-you-go API keys:

export DEEPINFRA_API_KEY="your-key"       # DeepInfra — open models (LLaMA, Qwen, etc.)
export OPENAI_API_KEY="sk-proj-..."       # OpenAI GPT-4o
export GEMINI_API_KEY="AIza..."           # Google Gemini — free tier available

Or store keys in ~/.AgentCrew/config.json:

{
  "api_keys": {
    "OPENAI_API_KEY": "sk-proj-..."
  }
}

Custom providers:

Custom providers such as Ollama, llama.cpp, and LM Studio are configured in the same ~/.AgentCrew/config.json file. See Custom LLM Providers for the full schema, llama.cpp configuration, model capabilities, and sampling options.

All supported providers:

Provider Cost profile Best for
OpenCode Go Subscription-based Curated open-source models, no API key
Command Code Subscription-based Frontier models via subscription
DeepInfra Pay-as-you-go, low cost Open models (LLaMA, Qwen, etc.)
Together AI Pay-as-you-go Open models, fine-tuning
Fireworks Pay-as-you-go Fast open model inference
OpenAI Per-token pricing GPT-4o, broad ecosystem
Anthropic Per-token pricing Claude family
Google Gemini Free tier available Budget-friendly, strong reasoning
GitHub Copilot Included with subscription Coding-focused, no extra cost
ChatGPT Codex Included with Plus/Pro sub No extra cost for subscribers
Custom Free (local) Fully offline (Ollama, llama.cpp...)

Which provider should I pick?

If you... Pick this
Want curated open-source models OpenCode Go — subscription-based
Want low-cost, open-source friendly DeepInfra
Have a Command Code subscription Command Code
Have ChatGPT Plus / Pro openai_codex — no extra cost
Have GitHub Copilot github_copilot — no extra cost
Want a free tier to start Google Gemini
Need fully offline / air-gapped Custom (Ollama, llama.cpp, etc.)

3. Launch

# Desktop GUI (default)
agentcrew chat

# Terminal mode — great for SSH, tmux, low-resource environments
agentcrew chat --console

On the first launch, AgentCrew walks you through creating your first agent.

4. Create your first agent

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

> /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.

The @AgentName syntax hands off a subtask to another agent. The receiving agent picks up with full context and its own specialized tools and instructions.


What's in the box?

Four ways to use AgentCrew

Mode Command Best for
Desktop GUI agentcrew chat Daily work, drag-and-drop files, visual diffs
Terminal agentcrew chat --console Remote servers, keyboard-first workflows
One-shot jobs agentcrew job --agent "Name" "task" ./files CI/CD, batch processing, automation
HTTP API agentcrew a2a-server Integrate with other apps, multi-instance agent networks

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

Tools — enable only what each agent needs

Tool What it does When to enable it
code_analysis Read files, grep, analyze repo structure Any agent working with code
file_editing Write/modify files (search-replace blocks, backups) Coding and documentation agents
web_search Search the web via Tavily Research and fact-checking agents
fetch_webpage Extract content from a URL Research agents
browser Full browser automation (navigate, click, form fill) QA, web scraping, form-filling agents
command_execution Run shell commands (rate limits, audit logs) DevOps, code execution agents
memory Store and retrieve conversation context Almost every agent
clipboard Read/write system clipboard Agents that interact with other apps
adaptive_learning Learn behavioral patterns from interactions Agents that should adapt over time
voice Speak and listen (ElevenLabs or DeepInfra) Voice-interactive agents
MCP tools External tools via Model Context Protocol Any agent needing external integrations
transfer Hand off tasks to other agents Automatically available in multi-agent setups

Communication protocols

AgentCrew speaks three protocols:

  • Console / GUI — Human-to-agent: the chat interface you use daily.
  • A2A (Agent-to-Agent) — HTTP+JSON-RPC protocol. Connect multiple AgentCrew instances so one can delegate to agents on another machine.
  • ACP (Agent Communication Protocol) — WebSocket protocol for custom clients, IDE integrations, and headless agent control.

Real-world workflows

🧑‍💻 Feature development — from idea to PR

You: @Architect  Design the data model for a multi-tenant SaaS app
     @Coding     Implement it with SQLAlchemy
     @Reviewer   Review the code for security issues

Three agents, one conversation. The Architect thinks about trade-offs, the Coder implements cleanly, the Reviewer catches blind spots.

📊 Financial report generation

# Five specialized agents, each focused on one step
[[agents]]  name = "FinancialDataExtractor"   # parse raw statements
[[agents]]  name = "RatioAnalyst"             # compute key ratios
[[agents]]  name = "TrendAnalyst"             # spot patterns over time
[[agents]]  name = "RiskAssessor"             # flag red flags
[[agents]]  name = "ReportingSynthesizer"     # compile into final report

Each agent handles one step of the pipeline. The Synthesizer collects all findings and writes the final report. See examples/agents/agents-financial-report.toml.

🌐 Multi-instance agent network

# Server A — hosts research agents
server-a$ agentcrew a2a-server --port 41241

# Server B — hosts coding agents
server-b$ agentcrew a2a-server --port 41241

# Your machine — connects to both
# ~/.AgentCrew/agents.toml:
[[remote_agents]]
name = "RemoteResearcher"
url = "http://server-a:41241"

[[remote_agents]]
name = "RemoteCoder"
url = "http://server-b:41241"

Common commands (once you're inside)

Command What it does
/agent <name> Switch to another agent
@<name> <task> Hand off a subtask
/clear Start a fresh conversation
/file <path> Attach a file
/think <low|medium|high|xhigh> Enable extended reasoning
/model <provider/model> Switch AI model
/voice Toggle voice recording
/help Show all commands
exit or quit Exit
Ctrl+C Stop the current response

Next steps


License

Apache 2.0 License. See LICENSE for details.

README fetched from the repository 6 hours ago. The original is authoritative.

Questions

About Agentcrew

How do I install Agentcrew?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Agentcrew safe to use with an AI agent?

Its trust score is 83 out of 100 (excellent). It passes 4 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Agentcrew still maintained?

Yes — the latest release is v0.22.0 (16 Oct 2026), and the last commit was yesterday. The repository has 219 stars and 1 open issues.