docker run -it -p8000:8000 \
  -v ~/.aws:/home/appuser/.aws:ro \
  -e MODEL_API_TYPE=Bedrock \
  -e AWS_PROFILE=AWSAdministratorAccess-880502554482 \
  -e FASTMCP_HOST=0.0.0.0 \
  709825985650.dkr.ecr.us-east-1.amazonaws.com/synechron/mcp-text2sql:0.0.10-2025.07.04-rc3 server

docker run -it \
    -v ~/.aws:/home/appuser/.aws:ro \
    -e AWS_PROFILE=AWSAdministratorAccess-880502554482 \
    -e BEDROCK_MODEL_ID=us.anthropic.claude-3-7-sonnet-20250219-v1:0 \
    -e BEDROCK_API_VERSION=2025-01-01-preview \
    -e MCP_SERVER_HOST=host.docker.internal \
     709825985650.dkr.ecr.us-east-1.amazonaws.com/synechron/mcp-text2sql:0.0.10-2025.07.04-rc3 client

Connected to server with tools: ['Text2Sql_Cyber_Threats', 'Text2Sql_ESG_Ratings']

MCP Client Started!
Type your queries or 'quit' to exit.

Query: What kind of data is in the Cyber Threat datasource?

The Cyber Threat datasource contains comprehensive information about cybersecurity incidents with the following data fields:

1. country - The country where the cyber attack took place
2. year - The year when the cyber attack occurred
3. attack_type - The type of cyber attack (e.g., Phishing, Ransomware, DDoS, Man-in-the-Middle, SQL Injection)
4. target_industry - The industry that was targeted (e.g., Education, Retail, IT, Telecommunications, Healthcare, Government, Banking)
5. financial_loss_(in_million_$) - The financial impact of the attack in millions of dollars
6. number_of_affected_users - How many users were affected by the attack
7. attack_source - Where the attack originated from (e.g., Hacker Group, Nation-state, Insider, Unknown)
8. security_vulnerability_type - The type of security vulnerability exploited (e.g., Unpatched Software, Weak Passwords, Social Engineering)
9. defense_mechanism_used - What defense was in place (e.g., VPN, Firewall, Antivirus, AI-based Detection)
10. incident_resolution_time_(in_hours) - How long it took to resolve the incident in hours

The database tracks cybersecurity incidents across different countries, industries, and years, including details about attack methods, financial impact, affected users, vulnerabilities exploited, and resolution times.

{
  "servers": {
    "text2sql": {
      "type": "streamable-http",
      "url": "http://localhost:8000/mcp"
    }
  }
}

{
  "mcpServers": {
    "text2sql": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--env-file",
        ".env",
        "709825985650.dkr.ecr.us-east-1.amazonaws.com/synechron/mcp-text2sql:0.0.10-2025.07.04-rc3",
        "server"
      ]
    }
  }
}

LOG_LEVEL=INFO
PYTHONUNBUFFERED=1
TEXT2SQL_VALVES_JSON=/home/appuser/config/config.json

MODE=shttp
FASTMCP_HOST=0.0.0.0
FASTMCP_PORT=8000

AUTH_ENABLED=true
AUTH_JWKS_URI=https://cognito-idp.us-east-1.amazonaws.com/us-east-1_/.well-known/jwks.json
AUTH_ISSUER=https://cognito-idp.us-east-1.amazonaws.com/us-east-1_

AWS_PROFILE=default

{
  "ENABLED": true,
  "ENABLE_RAG": false,
  "ENABLE_MARKDOWN": true,
  "ENABLE_PANDAS": true,
  "ENABLE_TABLE_INDEXING": true,
  "FORCE_REINDEXING": false,
  "DATABASE_CONFIG": {
    "Cyber_Threats": {
      "description": "A comprehensive dataset tracking cybersecurity incidents, attack vectors, threat types, and affected countries.",
      "topics": [
        "Cyber Threats",
        "Attacks",
        "Targets"
      ],
      "url": "sqlite:///file:/home/appuser/config/cyber_threats.db?uri=true",
      "tables": {
        "cyber_threats": "The Global Cybersecurity Threats Dataset (2015-2024) provides extensive data on cyberattacks, malware types, targeted industries, and affected countries."
      },
      "prompts": [
        {
          "name": "biggest_cyber_threat",
          "description": "Which type of cyber threat has caused the biggest financial loss?"
        }
      ]
    },
    "ESG_Ratings": {
      "description": "S&P 500 Companies ESG Insights & Risk Scores for Informed Decisions.",
      "topics": [
        "ESG Ratings",
        "ESG Risk",
        "Sustainability"
      ],
      "url": "sqlite:///file:/home/appuser/config/esg_ratings.db?uri=true",
      "tables": {
        "esg_ratings": "A comprehensive dataset tracking ESG ratings for S&P 500 companies."
      }
    }
  },
  "IGNORE_SCHEMA": "information_schema, INFORMATION_SCHEMA, _rsc, db_accessadmin, db_backupoperator, db_datareader, db_datawriter, db_ddladmin, db_denydatareader, db_denydatawriter, db_owner, db_securityadmin, guest, queryinsights, sys, pg_catalog",
  "MODEL_API_TYPE": "Bedrock",
  "AWS_PROFILE": "default",
  "API_VERSION": "2025-01-01-preview",
  "LLM_MODEL_NAME": "us.anthropic.claude-3-7-sonnet-20250219-v1:0",
  "EMBED_MODEL_NAME": "amazon.titan-embed-text-v2:0",
  "MAX_RETRY": 3,
  "MAX_RESULTS": 100,
  "MAX_DATAFRAME": 2000,
  "LOG_LEVEL": "INFO"
}