Name | vibeteam JSON |
Version |
0.1.1
JSON |
| download |
home_page | None |
Summary | MCP server for orchestrating sub-agents based on query analysis |
upload_time | 2025-08-08 20:43:01 |
maintainer | None |
docs_url | None |
author | None |
requires_python | >=3.10 |
license | MIT |
keywords |
agents
ai
claude
mcp
orchestration
|
VCS |
 |
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
No coveralls.
|
# Vibeteam
An MCP (Model Context Protocol) server that intelligently orchestrates sub-agents based on query analysis and project context.
## Features
- **Query Analysis**: Understands user intent (build, debug, feature, refactor, research, etc.)
- **Project Detection**: Automatically identifies project type (backend, frontend, fullstack, library)
- **Smart Agent Orchestration**: Deploys specialized agents based on project context and query intent
- **Parallel Execution**: Runs multiple agents concurrently for faster results
- **Tool Detection**: Automatically adapts to Cursor, Windsurf, VS Code, Claude Desktop, etc.
- **Multi-Agent Support**:
- Backend Specialist
- Frontend Specialist
- Web Researcher
- Code Analyzer
- Test Engineer
- DevOps Specialist
## Installation
### Via uvx (Recommended)
Once published to PyPI, you can install and run directly with uvx:
```bash
uvx vibeteam
```
### Via pip
```bash
pip install vibeteam
```
### From Source
```bash
git clone https://github.com/XiaoConstantine/vibeteam.git
cd vibeteam
uv sync
uv run vibeteam
```
## MCP Configuration
Add to your Claude Desktop or MCP client configuration:
```json
{
"servers": {
"vibeteam": {
"command": "uvx",
"args": ["vibeteam"]
}
}
}
```
Or if installed via pip:
```json
{
"servers": {
"vibeteam": {
"command": "vibeteam"
}
}
}
```
## Usage
### As MCP Server
The server runs as an MCP server and exposes tools for Claude or other MCP clients:
```bash
# Run with uvx
uvx vibeteam
# Or if installed
vibeteam
```
### Testing
```bash
uv run python test_server.py
```
## Tools Available
1. **analyze_and_orchestrate**: Main orchestration tool that analyzes query and deploys agents
2. **analyze_project**: Analyzes project structure and technology stack
3. **analyze_query**: Determines query intent and complexity
## How It Works
1. **Project Analysis**: Scans the current working directory to understand project structure
2. **Query Understanding**: Analyzes user query to determine intent and complexity
3. **Agent Planning**: Based on project type and query intent, plans appropriate agents
4. **Orchestration**: Executes agents in priority order and collects results
5. **Summary**: Provides consolidated output from all agents
## Architecture
The orchestrator uses a sophisticated analysis system to:
- Detect backend (Python, Go, Java, etc.) and frontend (React, Vue, Angular) technologies
- Understand query complexity and required expertise
- Deploy agents with appropriate priority levels
- Coordinate multi-agent workflows for complex tasks
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