MCP-AI-swarm
Verified Safeby bigmonmulgrew
Overview
An AI orchestration and microservices framework designed to route, manage, and distribute LLM requests to various AI backends for tasks like data extraction from unstructured text and generating visual output.
Installation
docker compose up --buildEnvironment Variables
- OLLAMA_HOST
- OLLAMA_PORT_E
- OLLAMA_PORT_I
- OLLAMA_MODEL_STORAGE
- OLLAMA_URL
- OLLAMA_DEFAULT_MODEL
- AI_MAX_CONCURRENT
- AI_QUEUE_URL
- MCPS_HOST
- MCPS_PORT_I
- MCPS_PORT_E
- MCP_DATA_HOST
- MCP_DATA_PORT_E
- MCP_DATA_URL
- MCP_VISUALISER_HOST
- MCP_VISUALISER_PORT_E
- MCP_VISUALISER_URL
- MCP_VERDICT_PORT_E
- NVIDIA_VISIBLE_DEVICES
- NVIDIA_DRIVER_CAPABILITIES
- FRONTEND_PORT_E
Security Notes
The `setup_envs.py` script uses `subprocess.run(..., shell=True)` which can be a security risk if the `cmd` or `cwd` arguments are derived from untrusted input. However, in this specific context, the commands are hardcoded or constructed from internal paths, mitigating immediate exploitability for the setup script itself. The main server components (FastAPI) use Pydantic for request body validation, which helps prevent injection attacks. No direct 'eval' or obvious hardcoded secrets are present in the core application logic. Inter-service communication is via HTTP, suggesting a need for proper network isolation and authentication mechanisms in a production environment.
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