Synechron Text2SQL MCP Server

Provides natural language access to relational databases using advanced language models, supporting multiple database types.

Synechron's Text2SQL MCP Server is aModel Context Protocol(MCP) server. It provides MCP clients like Cursor, VSCode, and Claude Desktop, with natural language access to relational databases of various types – enabling users to ask questions of their data using natural language capabilities.

Note: To use your own databases, further configuration is required, see theConfigurationsection below.

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.

Using the Server with an Existing MCP Client

The server should be run with Docker. Use either of the following configurations to add it to a MCP client:

{ "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" ] } } }

The Text2SQL MCP server can be configured with a combination of environment variables and JSON configuration.

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

Example TEXT2SQL_VALVES_JSON (valves.json)

The Text2SQL MCP server must be configured using a JSON file that specifies database connections, model settings, and other parameters. Here's an example configuration:

{ "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" }

The following environment variables can be provided to the sample MCP client:

The Text2SQL MCP server dynamically creates MCP Tools and Prompts for the configured databases in the following format:

- Text2Sql_DatabaseName: Query a specific database using natural language

- Parameters:

- query: Natural language query to execute against the database

This project is licensed under the MIT License.

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