claude-team-mcp
mcp
Uyari
Health Gecti
- License รขโฌโ License: MIT
- Description รขโฌโ Repository has a description
- Active repo รขโฌโ Last push 0 days ago
- Community trust รขโฌโ 50 GitHub stars
Code Uyari
- process.env รขโฌโ Environment variable access in src/__tests__/custom-experts.test.ts
Permissions Gecti
- Permissions รขโฌโ No dangerous permissions requested
Purpose
This tool is a Multi-Agent MCP Server that orchestrates multiple AI models (like GPT, Claude, and Gemini) to collaborate on complex software development tasks as a virtual team.
Security Assessment
Overall risk: Medium. The server acts as a router, making network requests to external AI APIs based on your configuration. It requires API keys to function, which you must supply via environment variables (e.g., `CLAUDE_TEAM_MAIN_KEY`) in your IDE's MCP configuration. There are no hardcoded secrets in the codebase. The automated scan flags environment variable access in the test files, which is a standard practice for loading test configurations rather than a vulnerability. The tool does not request dangerous local permissions and does not appear to execute arbitrary shell commands. However, because it handles your API keys and routes instructions to external models, standard caution is advised.
Quality Assessment
The project is highly active and exhibits strong quality indicators. It was updated very recently (last push was today), uses the permissive MIT license, and features a comprehensive README with clear documentation. The repository has garnered 50 GitHub stars, indicating a healthy level of community interest and early trust. Additionally, the tool boasts a robust automated test suite with 155 passed tests.
Verdict
Safe to use, provided you are comfortable configuring your personal API keys in your local IDE's settings to enable external network requests.
This tool is a Multi-Agent MCP Server that orchestrates multiple AI models (like GPT, Claude, and Gemini) to collaborate on complex software development tasks as a virtual team.
Security Assessment
Overall risk: Medium. The server acts as a router, making network requests to external AI APIs based on your configuration. It requires API keys to function, which you must supply via environment variables (e.g., `CLAUDE_TEAM_MAIN_KEY`) in your IDE's MCP configuration. There are no hardcoded secrets in the codebase. The automated scan flags environment variable access in the test files, which is a standard practice for loading test configurations rather than a vulnerability. The tool does not request dangerous local permissions and does not appear to execute arbitrary shell commands. However, because it handles your API keys and routes instructions to external models, standard caution is advised.
Quality Assessment
The project is highly active and exhibits strong quality indicators. It was updated very recently (last push was today), uses the permissive MIT license, and features a comprehensive README with clear documentation. The repository has garnered 50 GitHub stars, indicating a healthy level of community interest and early trust. Additionally, the tool boasts a robust automated test suite with 155 passed tests.
Verdict
Safe to use, provided you are comfortable configuring your personal API keys in your local IDE's settings to enable external network requests.
๐ค Multi-Agent MCP Server - Let Claude Code / Windsurf / Cursor orchestrate GPT, Claude, Gemini to work as an AI dev team
README.md
๐ค Claude Team
Multi-Agent MCP Server for AI-Powered Development Teams
Orchestrate GPT, Claude, Gemini and more to collaborate on complex tasks
โจ Features
| Feature | Description |
|---|---|
| ๐ค Multi-Model Collaboration | Configure multiple AI models to work together, each leveraging their strengths |
| ๐ง Smart Task Distribution | Tech Lead analyzes tasks and automatically assigns them to the best-suited experts |
| ๐ Workflow Templates | 5 pre-built workflows: code generation, bug fixing, refactoring, review, documentation |
| ๐ฏ Custom Experts | Define your own experts (Rust, K8s, Security, etc.) via environment variables |
| ๐ Observability | Dashboard, cost estimation, and task planning preview |
| ๐ Proxy API Support | Custom Base URLs, compatible with various proxy services |
| ๐ Collaboration History | Complete record of all collaborations with search support |
๐ Quick Start
Installation
# Global install
npm install -g claude-team
# Or use directly with npx (no install needed)
npx claude-team
Basic Configuration
Add to your IDE's MCP configuration file:
๐ Configuration File Locations| IDE | Path |
|---|---|
| Claude Code | ~/.claude/config.json |
| Windsurf | ~/.codeium/windsurf/mcp_config.json |
| Cursor | ~/.cursor/mcp.json |
{
"mcpServers": {
"claude-team": {
"command": "npx",
"args": ["-y", "claude-team"],
"env": {
"CLAUDE_TEAM_MAIN_KEY": "sk-your-api-key",
"CLAUDE_TEAM_MAIN_URL": "https://api.openai.com/v1",
"CLAUDE_TEAM_MAIN_MODEL": "gpt-4o",
"CLAUDE_TEAM_MAIN_PROVIDER": "openai"
}
}
}
}
Start Using
> Help me build a user login feature with the team
> Have the team optimize this code for performance
๐ฌ How It Works
User: "Optimize this SQL query for performance"
Tech Lead Analysis โ
โโโ Creates: SQL Optimization Expert (powerful)
โโโ Creates: Index Analysis Expert (balanced)
โโโ Workflow: sequential
User: "Build a settings page with dark mode"
Tech Lead Analysis โ
โโโ Creates: UI Component Expert (balanced)
โโโ Creates: Theme System Expert (fast)
โโโ Creates: State Management Expert (balanced)
โโโ Workflow: parallel โ review
๐ ๏ธ Available Tools
Core Tools
| Tool | Description |
|---|---|
team_work |
๐ Team collaboration (auto-creates experts) |
ask_expert |
๐ฌ Consult an expert (supports custom experts) |
code_review |
๐ Code review |
fix_bug |
๐ Bug fixing |
Workflow Tools
| Tool | Description |
|---|---|
list_workflows |
๐ List all workflow templates |
run_workflow |
โถ๏ธ Execute a specific workflow |
suggest_workflow |
๐ก Auto-recommend workflow based on task |
Pre-built Workflows:
| Workflow | Purpose | Steps |
|---|---|---|
code-generation |
Generate code from requirements | Design โ Implement โ Test โ Review |
bug-fix |
Diagnose and fix bugs | Diagnose โ Fix โ Verify |
refactoring |
Code refactoring | Analyze โ Plan โ Execute โ Review |
code-review |
Multi-dimensional review | Security / Quality / Performance (parallel) |
documentation |
Generate documentation | Analyze โ Document |
Observability Tools
| Tool | Description |
|---|---|
team_dashboard |
๐๏ธ View team status, experts, models, stats |
cost_estimate |
๐ฐ Estimate task cost (tokens, price, time) |
explain_plan |
๐ง Preview task assignment plan |
usage_stats |
๐ View model usage statistics |
Integration Tools
| Tool | Description |
|---|---|
read_project_files |
๐ Read project files for context |
analyze_project_structure |
๐๏ธ Analyze project structure and tech stack |
generate_commit_message |
๐ Generate commit message from diff |
History Tools
| Tool | Description |
|---|---|
history_list |
๐ View collaboration history |
history_get |
๐ Get history details |
history_search |
๐ Search history records |
history_context |
๐ Get recent context |
โ๏ธ Configuration
Environment Variables
| Variable | Required | Description |
|---|---|---|
CLAUDE_TEAM_MAIN_KEY |
โ | Main model API Key |
CLAUDE_TEAM_MAIN_URL |
โ | Main model API URL |
CLAUDE_TEAM_MAIN_MODEL |
โ | Main model ID (default: gpt-4o) |
CLAUDE_TEAM_MAIN_PROVIDER |
โ | Provider: openai / anthropic / gemini |
CLAUDE_TEAM_MODEL{N}_* |
โ | Worker model N config (inherits from MAIN) |
CLAUDE_TEAM_CUSTOM_EXPERTS |
โ | Custom experts (JSON format) |
N = 1, 2, 3... supports up to 10 worker models
Custom Experts
Define your own experts beyond the built-in frontend, backend, qa:
{
"env": {
"CLAUDE_TEAM_CUSTOM_EXPERTS": "{\"rust\":{\"name\":\"Rust Expert\",\"prompt\":\"You are a Rust expert...\",\"tier\":\"powerful\"},\"k8s\":{\"name\":\"K8s Expert\",\"prompt\":\"You are a Kubernetes expert...\",\"tier\":\"balanced\"}}"
}
}
| Field | Required | Description |
|---|---|---|
name |
โ | Expert display name |
prompt |
โ | Expert role description (System Prompt) |
tier |
โ | Model tier: fast / balanced / powerful |
skills |
โ | Skill tags array |
Model Tiers
| Tier | Use Case | Example Scenarios |
|---|---|---|
fast |
Simple, quick tasks | Formatting, simple queries, docs |
balanced |
Regular dev tasks | Components, APIs, unit tests |
powerful |
Complex reasoning | Architecture, optimization, security |
๐ฆ Changelog
v0.4.0
- ๐ฏ Custom Experts - Define experts via environment variables
- ๐ Workflow Templates - 5 pre-built workflows
- ๐ Observability - Dashboard, cost estimation, plan preview
- ๐ Integration - Project file reading, structure analysis, commit messages
- ๐ก Smart Recommendations - Auto-suggest workflows
- ๐งช Test Coverage - 155 test cases
v0.3.0
- ๐ Task interrupt/resume support
- ๐ฌ Multi-turn expert conversations
- ๐ Token counting and cost estimation
- ๐ Expert templates (6 built-in + custom)
- ๐ Webhook notifications
- โก Exponential backoff retry
- ๐ง Hot config reload
v0.2.x
- ๐ Streaming output support
- ๐ Usage statistics
- ๐ฏ Model strategies
- ๐พ Result caching
- ๐ Auto model switching
v0.1.x
- ๐ Initial release
- ๐ค Multi-model collaboration
- ๐ Proxy API support
๐ค Contributing
Contributions are welcome! Please read our:
๐ License
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