dcisionai-mcp-platform
by ameydhavle
Overview
Exposes AI-powered optimization capabilities via a Model Context Protocol (MCP) and REST/WebSocket APIs, enabling seamless integration with various enterprise platforms and AI assistants for natural language problem solving and model execution.
Installation
python dcisionai_mcp_server/start_mcp_server.pyEnvironment Variables
- ANTHROPIC_API_KEY
- MISTRAL_API_KEY
- DEEPSEEK_API_KEY
- DCISIONAI_API_URL
- DCISIONAI_API_KEY
- CLAUDE_MODEL
- SUPABASE_URL
- SUPABASE_ANON_KEY
- DCISIONAI_REQUEST_TIMEOUT
- DCISIONAI_ASYNC_ENABLED
- DCISIONAI_LOG_LEVEL
- DCISIONAI_DOMAIN_FILTER
- WREN_API_URL
- WREN_API_KEY
Security Notes
CRITICAL: The codebase uses `eval` and `exec` in multiple places (e.g., `dcisionai_graph/dame/formula_interpreter.py`, `dcisionai_graph/dame/constraint_encoder.py`, `dcisionai_graph/core/tools/formula/pyomo_generator.py`) to process LLM-generated code or potentially user-provided formulas. Without rigorous, explicit sanitization or a robust allowlisting mechanism, this constitutes a severe Remote Code Execution (RCE) vulnerability. Additionally, `dcisionai_graph/ui/src/agentcore-config.js` contains hardcoded AWS/Cognito access tokens and client secrets, which is a critical security flaw for any deployed application.
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