aiAgents_database
by Srinivs-p
Overview
Intelligent database querying system enabling natural language interaction with Oracle databases via AI agents, vector search, and Retrieval-Augmented Generation (RAG).
Installation
python example_mcp_server.pyEnvironment Variables
- LLM_API_KEY
- LLM_MODEL
- LLM_PROVIDER
- EMBEDDING_MODEL
- CHUNK_SIZE
- CHUNK_OVERLAP
- TOP_K_RESULTS
- MCP_SERVER_URL
- MCP_SERVER_PORT
- VECTOR_DB_TYPE
Security Notes
CRITICAL: The MCP server in `mcp/server.py` contains severe SQL injection vulnerabilities in `_handle_query_database` and `_handle_execute_sql` methods. User-provided `query` and `sql` parameters are directly executed via `cursor.execute()` without sanitization or proper parameterization, allowing arbitrary SQL code execution. Additionally, Oracle database credentials are expected to be hardcoded into `db_engine.py` (copied from `db_engine.example.py`), which is a significant security anti-pattern for secret management. The `config/settings.py` also validates for `VECTOR_DB_URL` as required, but the default `chroma` setup in `.env.example` does not provide it, indicating a potential configuration discrepancy or security oversight if other vector DBs are used without proper URL validation.
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