Multi Database MCP Server

A powerful multi-database server implementing the Model Context Protocol (MCP) to provide AI assistants with structured access to databases.

Overview • Core Concepts • Features • Supported Databases • Deployment Options • Configuration • Available Tools • Examples • Troubleshooting • Contributing

📄 Product Requirements — current capabilities, roadmap & decisions

Overview

The DB MCP Server provides a standardized way for AI models to interact with multiple databases simultaneously. Built on the FreePeak/cortex framework, it enables AI assistants to execute SQL queries, manage transactions, explore schemas, and analyze performance across different database systems through a unified interface.

Core Concepts

Multi-Database Support

Unlike traditional database connectors, DB MCP Server can connect to and interact with multiple databases concurrently:

{
  "connections": [
    {
      "id": "mysql1",
      "type": "mysql",
      "host": "localhost",
      "port": 3306,
      "name": "db1",
      "user": "user1",
      "password": "password1"
    },
    {
      "id": "postgres1",
      "type": "postgres",
      "host": "localhost",
      "port": 5432,
      "name": "db2",
      "user": "user2",
      "password": "password2"
    },
    {
      "id": "oracle1",
      "type": "oracle",
      "host": "localhost",
      "port": 1521,
      "service_name": "XEPDB1",
      "user": "user3",
      "password": "password3"
    }
  ]
}

Dynamic Tool Generation

For each connected database, the server automatically generates specialized tools:

// For a database with ID "mysql1", these tools are generated:
query_mysql1       // Execute SQL queries
execute_mysql1     // Run data modification statements
transaction_mysql1 // Manage transactions
schema_mysql1      // Explore database schema
performance_mysql1 // Analyze query performance

Clean Architecture

The server follows Clean Architecture principles with these layers:

1. Domain Layer: Core business entities and interfaces
2. Repository Layer: Data access implementations
3. Use Case Layer: Application business logic
4. Delivery Layer: External interfaces (MCP tools)

Features

• Simultaneous Multi-Database Support: Connect to multiple MySQL, PostgreSQL, SQLite, and Oracle databases concurrently
• Lazy Loading Mode: Defer connection establishment until first use - perfect for setups with 10+ databases (enable with --lazy-loading flag)
• Database-Specific Tool Generation: Auto-creates specialized tools for each connected database
• Clean Architecture: Modular design with clear separation of concerns
• OpenAI Agents SDK Compatibility: Full compatibility for seamless AI assistant integration
• Dynamic Database Tools: Execute queries, run statements, manage transactions, explore schemas, analyze performance
• Unified Interface: Consistent interaction patterns across different database types
• Connection Management: Simple configuration for multiple database connections
• Health Check: Automatic validation of database connectivity on startup
• Production Guardrails: Per-database read_only enforcement (blocks writes through both query_ and execute_ tools), max_rows result truncation with explicit notices, and per-query timeouts

Production Guardrails

Protect agent sessions against runaway queries and accidental writes:

| Setting | Scope | Effect | |---------|-------|--------| | "read_only": true | per database | Blocks write statements (INSERT, UPDATE, DELETE, DDL, data-modifying CTEs, stacked writes) through both query and execute tools, and enforces rejection at the database engine itself on PostgreSQL/TimescaleDB (default_transaction_read_only=on) and MySQL (transaction_read_only=1); SQLite opens mode=ro. Classification strips comments and string literals and defaults to deny for unrecognized statements. | | "max_rows": 1000 | per database | Truncates result sets at N rows and appends an explicit [Truncated] notice so the model knows to refine its query instead of losing context. 0 (default) means unlimited. | | "masking_rules": [...] | per database | Masks values of result columns whose name matches a rule's regex before they leave the server — applies to every query shape including SELECT *. Strategies: "fixed_string" (replace with value), "null", and "partial" (keep_last trailing characters visible; shorter values fully masked). First matching rule wins; invalid patterns or unknown strategies abort config load (fail closed); masked-cell counts are reported in the result footer. Renaming a column with an alias bypasses name matching by design. See docs/design/column-masking-scoping.md. | | "query_timeout": 30 | per database | Cancels statements that exceed the timeout in seconds; enforced at the repository layer for every tool (queries, statements, transactions, explain, schema inspection). Unset defaults to 30s; -1 disables. Env-only deployments can set QUERY_TIMEOUT_SECONDS to fill connections without an explicit value (JSON keeps precedence). |

| DB_MCP_AUDIT_LOG=/path/audit.jsonl | process | Appends one JSONL record per executed statement — timestamp, op (query/execute/tx_*), database, statement (capped at 10k chars), duration, error. Includes rejected attempts against read-only databases. Best-effort writes never fail a query; file is created with 0600. |

Defense in depth: read-only is enforced in three layers — application classifier, engine session defaults, and (recommended) least-privilege database users. Oracle currently relies on the classifier plus user privileges.

Supported Databases

| Database | Status | Features | | ---------- | ------------------------- | ------------------------------------------------------------ | | MySQL | ✅ Full Support | Queries, Transactions, Schema Analysis, Performance Insights | | PostgreSQL | ✅ Full Support (v9.6-17) | Queries, Transactions, Schema Analysis, Performance Insights | | SQLite | ✅ Full Support | File-based & In-memory databases, SQLCipher encryption support | | Oracle | ✅ Full Support (10g-23c) | Queries, Transactions, Schema Analysis, RAC, Cloud Wallet, TNS | | TimescaleDB| ✅ Full Support | Time-Series Queries, Hypertable Discovery (write policies via SQL) |

Deployment and transport status

The safest local integration is STDIO. HTTP transports are still under hardening; do not expose the current server directly to a shared network.

Personal/local STDIO (recommended)

# Build from the audited source revision
make build
Use a private, single-connection config
./bin/server -t stdio -c /absolute/path/to/config.local.json

For Cursor, point the client at the actual build output and use absolute paths:

{
  "mcpServers": {
    "local-db": {
      "command": "/absolute/path/to/db-mcp-server/bin/server",
      "args": ["-t", "stdio", "-c", "/absolute/path/to/config.local.json"]
    }
  }
}

Use a read-only database account and a bounded query_timeout for a personal PostgreSQL/MySQL connection. For SQLite, use an absolute database_path and "read_only": true when the agent only needs to inspect data.

Legacy SSE (compatibility only)

The historical Cortex SSE transport has no built-in authentication. It is disabled by default and must only be enabled explicitly behind a trusted private reverse proxy:

./bin/server -t sse -h 127.0.0.1 -p 9092 \
  -allow-insecure-sse -c /absolute/path/to/config.local.json

Do not use this mode for a shared deployment. The legacy endpoint does not apply DB_MCP_API_KEY; terminate TLS, authentication, and network policy at the proxy. A future release will replace it with a maintained Streamable HTTP implementation.

Streamable HTTP (experimental)

The streamable endpoint is backed by the maintained Go MCP SDK and supports stateful sessions, JSON or SSE responses, notifications, GET/DELETE session lifecycle, and JSON-RPC dispatch. The process refuses to start it without DB_MCP_API_KEY; keep it behind a private TLS gateway until the identity and conformance rollout is complete.

For browser-origin requests, set an explicit comma-separated allowlist:

MCP_ALLOWED_ORIGINS=https://agent.example.com

The built-in static bearer key is a bounded pilot mechanism. It grants db:read by default; set DB_MCP_API_SCOPES=db:read,db:write only for a trusted write client. db:admin is reserved for controlled administration. Set DB_MCP_OIDC_ISSUER and DB_MCP_OIDC_AUDIENCE to use OIDC discovery, JWKS signature validation, issuer/audience checks, and subject identity for shared deployments; database-specific scopes are still intentionally not enabled until that policy is defined.

Docker development image

The published image is a development/demo artifact, not an enterprise hardening recommendation. The current Dockerfile runs as an unprivileged user, omits an embedded config, and includes the legacy -allow-insecure-sse behavior for local Compose compatibility. It exposes a separate health port (9093) and is not suitable for public publication.

# Build a local image from this source revision
docker build -t db-mcp-server:local .
Keep it private; the image's default SSE mode is compatibility-only
docker run --rm -p 127.0.0.1:9092:9092 \
  -p 127.0.0.1:9093:9093 \
  -v "$(pwd)/config.local.json:/app/config.json:ro" \
  db-mcp-server:local

For a team deployment, wait for the authenticated Streamable transport and use a non-root, read-only-filesystem image with a private network, external secret store, and a TLS/OIDC gateway.

Source Code Installation

# Clone the repository
git clone https://github.com/FreePeak/db-mcp-server.git
cd db-mcp-server
Build the server
make build
Run the server
./bin/server -t stdio -c config.json

Configuration

Database Configuration File

Create a config.json file with your database connections. schema_version: 1 enables strict unknown-field validation:

{
  "schema_version": 1,
  "connections": [
    {
      "id": "mysql1",
      "type": "mysql",
      "host": "mysql1",
      "port": 3306,
      "name": "db1",
      "user": "user1",
      "password_env": "DB_MCP_MYSQL_PASSWORD",
      "query_timeout": 60,
      "max_open_conns": 20,
      "max_idle_conns": 5,
      "conn_max_lifetime_seconds": 300,
      "conn_max_idle_time_seconds": 60,
      "read_only": false,
      "max_rows": 1000,
      "masking_rules": [
        { "pattern": "(?i)email", "strategy": "fixed_string", "value": "MASKED" },
        { "pattern": "(?i)(ssn|tax_id)", "strategy": "null" }
      ]
    },
    {
      "id": "postgres1",
      "type": "postgres",
      "host": "postgres1",
      "port": 5432,
      "name": "db1",
      "user": "user1",
      "password_env": "DB_MCP_POSTGRES_PASSWORD"
    },
    {
      "id": "sqlite_app",
      "type": "sqlite",
      "database_path": "./data/app.db",
      "journal_mode": "WAL",
      "cache_size": 2000,
      "read_only": false,
      "use_modernc_driver": true,
      "query_timeout": 30,
      "max_open_conns": 1,
      "max_idle_conns": 1
    },
    {
      "id": "sqlite_encrypted",
      "type": "sqlite",
      "database_path": "./data/secure.db",
      "encryption_key": "your-secret-key-here",
      "journal_mode": "WAL",
      "use_modernc_driver": false
    },
    {
      "id": "sqlite_memory",
      "type": "sqlite",
      "database_path": ":memory:",
      "cache_size": 1000,
      "use_modernc_driver": true
    }
  ]
}

Secret references

Do not put production credentials directly in JSON. Use either an environment variable name or a mounted secret file per connection:

{
  "id": "prod",
  "type": "postgres",
  "host": "db.internal",
  "port": 5432,
  "name": "app",
  "user": "mcp_reader",
  "password_env": "DB_MCP_PROD_PASSWORD"
}

password_file and encryption_key_env/encryption_key_file are also supported. Relative file paths resolve from the config file directory; an inline value cannot be combined with a reference. The resolved value stays in process memory and is not printed by the config loader.

Command-Line Options

# Basic syntax
./bin/server -t <transport> -c <config-file>
HTTP transport options (legacy SSE requires an explicit opt-in)
./bin/server -t sse -h <hostname> -p <port> -allow-insecure-sse -c <config-file>
Lazy loading mode (recommended for 10+ databases)
./bin/server -t stdio -c <config-file> --lazy-loading
Customize log directory (useful for multi-project setups)
./bin/server -t stdio -c <config-file> -log-dir /tmp/db-mcp-logs
Inline database configuration
./bin/server -t stdio -db-config '{"connections":[...]}'
Environment variable configuration
export DB_CONFIG='{"connections":[...]}'
./bin/server -t stdio

Available Flags:

• -t, -transport: Transport mode (stdio, legacy sse, or experimental streamable)
• -c, -config: Path to database configuration file
• -p, -port: HTTP port (default: 9092)
• -h, -host: HTTP bind host (default: 127.0.0.1)
• -allow-insecure-sse: Explicitly allow legacy SSE for a private development proxy
• -api-key: Bearer key for the experimental Streamable HTTP entrypoint (or use DB_MCP_API_KEY)
• -health-port: HTTP health port (default: 9093; 0 disables it)
• -log-level: Log level (debug, info, warn, error)
• -log-dir: Directory for log files (default: ./logs in current directory)
• -db-config: Inline JSON database configuration
• -lazy-loading: Establish connections on first use
• -unified-tools: Register one tool set with a database parameter

Environment Variables

Values in a .env file are loaded first; real environment variables take precedence. A JSON config file (CONFIG_PATH/DB_CONFIG_FILE) takes precedence over inline and legacy database variables.

| Variable | Default | Purpose | |---|---|---| | CONFIG_PATH / DB_CONFIG_FILE | config.json | Path to the multi-database JSON config | | DB_CONFIG | — | Inline JSON database configuration (used when no file is present) | | TRANSPORT_MODE | stdio | Transport mode when -t is not passed | | SERVER_PORT | 9092 | HTTP port | | MCP_ALLOWED_ORIGINS | empty | Comma-separated browser origins allowed by experimental Streamable HTTP | | DB_MCP_API_KEY | empty | Bearer key for experimental Streamable HTTP; keep it in a secret manager | | DB_MCP_API_SCOPES | db:read | Required/granted scopes: db:read, db:write, and/or db:admin | | DB_MCP_OIDC_ISSUER | empty | OIDC issuer URL; when set, OIDC/JWT verification replaces the static pilot key | | DB_MCP_OIDC_AUDIENCE | empty | Required OIDC audience/client ID | | LOG_LEVEL | info | Log verbosity (debug, info, warn, error) | | DISABLE_LOGGING | false | true/1 silences logging entirely | | DB_TYPE, DB_HOST, DB_PORT, DB_USER, DB_PASSWORD, DB_NAME | engine defaults | Single-database fallback when no JSON config exists | | QUERY_TIMEOUT_SECONDS | unset | Fills connections that don't set their own query_timeout; negative disables the cap. JSON configs keep precedence. | | DB_MCP_AUDIT_LOG | unset | Optional append-only JSONL audit path |

SQLite Configuration Options

When using SQLite databases, you can leverage these additional configuration options:

SQLite Connection Parameters

| Parameter | Type | Default | Description | |-----------|------|---------|-------------| | database_path | string | Required | Path to SQLite database file or :memory: for in-memory | | encryption_key | string | - | Key for SQLCipher encrypted databases | | read_only | boolean | false | Open database in read-only mode | | max_rows | integer | unlimited | Maximum rows returned per query; larger results are truncated with an explicit notice. Works on all database types | | cache_size | integer | 2000 | SQLite cache size in pages | | journal_mode | string | "WAL" | Journal mode: DELETE, TRUNCATE, PERSIST, WAL, OFF | | use_modernc_driver | boolean | true | Use modernc.org/sqlite (CGO-free) or mattn/go-sqlite3 |

SQLite Examples

Basic File Database

{
  "id": "my_sqlite_db",
  "type": "sqlite",
  "database_path": "./data/myapp.db",
  "journal_mode": "WAL",
  "cache_size": 2000
}

Encrypted Database (SQLCipher)

{
  "id": "encrypted_db",
  "type": "sqlite",
  "database_path": "./data/secure.db",
  "encryption_key": "your-secret-encryption-key",
  "use_modernc_driver": false
}

In-Memory Database

{
  "id": "memory_db",
  "type": "sqlite",
  "database_path": ":memory:",
  "cache_size": 1000
}

Read-Only Database

{
  "id": "reference_data",
  "type": "sqlite",
  "database_path": "./data/reference.db",
  "read_only": true,
  "journal_mode": "DELETE"
}

Oracle Configuration Options

When using Oracle databases, you can leverage these additional configuration options:

Oracle Connection Parameters

| Parameter | Type | Default | Description | |-----------|------|---------|-------------| | host | string | Required | Oracle database host | | port | integer | 1521 | Oracle listener port | | service_name | string | - | Service name (recommended for RAC) | | sid | string | - | System identifier (legacy, use service_name instead) | | user | string | Required | Database username | | password | string | Required | Database password | | wallet_location | string | - | Path to Oracle Cloud wallet directory | | tns_admin | string | - | Path to directory containing tnsnames.ora | | tns_entry | string | - | Named entry from tnsnames.ora | | edition | string | - | Edition-Based Redefinition edition name | | pooling | boolean | false | Enable driver-level connection pooling | | standby_sessions | boolean | false | Allow queries on standby databases | | nls_lang | string | AMERICAN_AMERICA.AL32UTF8 | Character set configuration |

Oracle Examples

Basic Oracle Connection (Development)

{
  "id": "oracle_dev",
  "type": "oracle",
  "host": "localhost",
  "port": 1521,
  "service_name": "XEPDB1",
  "user": "testuser",
  "password": "testpass",
  "max_open_conns": 50,
  "max_idle_conns": 10,
  "conn_max_lifetime_seconds": 1800
}

Oracle with SID (Legacy)

{
  "id": "oracle_legacy",
  "type": "oracle",
  "host": "oracledb.company.com",
  "port": 1521,
  "sid": "ORCL",
  "user": "app_user",
  "password": "app_password"
}

Oracle Cloud Autonomous Database (with Wallet)

{
  "id": "oracle_cloud",
  "type": "oracle",
  "user": "ADMIN",
  "password": "your-cloud-password",
  "wallet_location": "/path/to/wallet_DBNAME",
  "service_name": "dbname_high"
}

Oracle RAC (Real Application Clusters)

{
  "id": "oracle_rac",
  "type": "oracle",
  "host": "scan.company.com",
  "port": 1521,
  "service_name": "production",
  "user": "app_user",
  "password": "app_password",
  "max_open_conns": 100,
  "max_idle_conns": 20
}

Oracle with TNS Entry

{
  "id": "oracle_tns",
  "type": "oracle",
  "tns_admin": "/opt/oracle/network/admin",
  "tns_entry": "PROD_DB",
  "user": "app_user",
  "password": "app_password"
}

Oracle with Edition-Based Redefinition

{
  "id": "oracle_ebr",
  "type": "oracle",
  "host": "oracledb.company.com",
  "port": 1521,
  "service_name": "production",
  "user": "app_user",
  "password": "app_password",
  "edition": "v2_0"
}

Oracle Connection String Priority

When multiple connection methods are configured, the following priority is used:

1. TNS Entry (if tns_entry and tns_admin are configured)
2. Wallet (if wallet_location is configured) - for Oracle Cloud
3. Standard (host:port/service_name) - default method

Available Tools

For each connected database, DB MCP Server automatically generates these specialized tools:

Query Tools

| Tool Name | Description | |-----------|-------------| | query_ | Execute SELECT queries and get results as a tabular dataset | | execute_ | Run data manipulation statements (INSERT, UPDATE, DELETE) | | transaction_ | Begin, commit, and rollback transactions |

Schema Tools

| Tool Name | Description | |-----------|-------------| | schema_ | Get information about tables, columns, indexes, and foreign keys | | generate_schema_ | Generate SQL or code from database schema |

Performance Tools

| Tool Name | Description | |-----------|-------------| | performance_ | Analyze query performance via actions: stats / slow_queries (in-process tracker), engine_slow_queries (pg_stat_statements / MySQL digest tables / Oracle v$sqlarea), suggest (static SQL lint), suggest_indexes (heuristic CREATE INDEX advice for one statement, equality-first composites, verify with EXPLAIN), validate_suggestions (PostgreSQL: installs the same suggestions as cost-free hypothetical indexes via the hypopg extension and reports whether the planner actually picks each one — ground-truth validation instead of manual EXPLAIN), workload_suggestions (same analysis across the top-N expensive workload statements, weighted by executions), index_health (duplicate/redundant/unused/invalid indexes and table bloat findings from catalogs; usage evidence where engine statistics exist), db_health (everything index_health covers plus connection-pressure utilization vs max_connections), reset | | explain_ | Show the execution plan for a SQL statement without running it; analyze: true executes with timing/buffer stats (PostgreSQL/MySQL). Writes stay blocked on read-only databases | | describe_ | Inspect one table's columns, indexes, and row estimate via engine catalog queries | | health_ | Report connectivity, ping latency, connection-pool state, and engine stats (PostgreSQL buffer-cache hit ratio, MySQL InnoDB buffer efficiency) |

TimescaleDB Tools

For PostgreSQL databases with the timescaledb extension installed, these additional specialized tools are registered automatically at startup (registration is config-driven, so it also works under --lazy-loading; each handler verifies the extension at call time and returns an actionable error when it is absent):

| Tool Name | Description | |-----------|-------------| | timescaledb_timeseries_query_ | Execute optimized time-series queries with time bucketing (time_bucket), filtering, and window functions | | timescaledb_analyze_timeseries_ | Analyze time-series patterns (trend, seasonality summary) for one table/column | | timescaledb_list_hypertables_ | List hypertables with their time column and dimension count (read-only) | | timescaledb_compression_settings_ | Show compression configuration for hypertables (read-only) | | timescaledb_retention_policy_ | Show configured retention policies (read-only) | | timescaledb_list_continuous_aggregates_ | List continuous aggregates with bucket interval and refresh policy (read-only) | | timescaledb_continuous_aggregate_info_ | Inspect one continuous aggregate in detail (read-only) |

In unified mode the same seven tools appear once as timescaledb_timeseries_query, timescaledb_analyze_timeseries, timescaledb_list_hypertables, timescaledb_compression_settings, timescaledb_retention_policy, timescaledb_list_continuous_aggregates, and timescaledb_continuous_aggregate_info, each taking a required database parameter.

Scope note: read-only discovery above goes through the query pipeline and therefore

stays usable on read_only databases; each handler checks for the timescaledb

extension first. Write-policy operations (hypertable creation, compression toggles,

add/remove retention or refresh policies) remain unexposed — use plain SQL through

the query/execute tools in the meantime. For detailed documentation, see

TIMESCALEDB_TOOLS.md.

Unified Tool Mode

If you connect many databases (5+), the per-database tool naming generates a large number of tools (5 × N). Some MCP clients — Claude in particular — apply strict limits on the total number of tools and tool description size that can cause the agent to fail to load the server, ignore tools, or refuse to call them. Issue #18 documents this exact symptom: "the db-mcp-server does not function properly with Claude, even though it works fine with OpenAI".

For these clients, launch the server with the --unified-tools flag to register six consolidated tools (query, execute, transaction, performance, explain, describe, schema, filter_tables) instead of per-database tools:

./bin/server -t stdio -c config.json --unified-tools

Context-window cost (measured, TestToolTokenBenchmark, re-verified 2026-08 via scripts/token-benchmark.sh): unified mode costs ~1.25–1.6k tokens regardless of how many databases are connected, while per-database mode costs ~800 tokens per database (7 tools each) — 10 connected databases ≈ 8k tokens, an 80% wire-payload saving with unified. With one database only, per-database naming is slightly cheaper; unified wins from two databases onward and scales flat thereafter. Re-measure the real wire payload yourself with scripts/token-benchmark.sh; methodology and results in docs/benchmark-token-efficiency.md.

In unified mode, each tool accepts a required database parameter that names
which database the call should target. See the Configuration
section for the full list of available databases. This dramatically reduces the
tool count and the cumulative description size, which resolves the Claude
compatibility issues.

For very large configurations, also enable --lazy-loading so that startup
doesn't open connections to databases that may never be queried during the
session.
Examples
Querying Multiple Databases

-- Query the PostgreSQL database in the same context query_postgres1("SELECT * FROM products WHERE price > 100")

-- Query the SQLite database query_sqlite_app("SELECT * FROM local_data WHERE created_at > datetime('now', '-1 day')")

-- Query the Oracle database query_oracle_dev("SELECT * FROM employees WHERE hire_date > SYSDATE - 30")

### Managing Transactions

The transaction_<db_id> tool supports begin, execute, commit, and rollback actions. Each begin returns a transactionId; pass it back to stage statements and to commit or roll back:

// 2. Execute statements within the transaction { "action": "execute", "transactionId": "tx_mysql1_1730000000000000000", "statement": "INSERT INTO orders (customer_id, product_id) VALUES (1, 2)" }

// 3a. Commit — persists all staged statements { "action": "commit", "transactionId": "tx_mysql1_1730000000000000000" }

// 3b. OR rollback — discards all staged statements { "action": "rollback", "transactionId": "tx_mysql1_1730000000000000000" }

Unknown or already-retired transaction IDs return a clear error instead of a silent success, so agents can detect and recover from lost-transaction situations.

Exploring Database Schema

-- Get columns for a specific table schema_mysql1("columns", "users")

-- Get constraints schema_mysql1("constraints", "orders")

### Working with SQLite-Specific Features

-- Use SQLite-specific date functions query_sqlite_app("SELECT * FROM events WHERE date(created_at) = date('now')")

-- Query SQLite master table for schema information query_sqlite_app("SELECT name, sql FROM sqlite_master WHERE type='table' AND name NOT LIKE 'sqlite_%'")

-- Performance optimization with WAL mode execute_sqlite_app("PRAGMA journal_mode = WAL") execute_sqlite_app("PRAGMA synchronous = NORMAL")

### Working with Oracle-Specific Features

-- Use Oracle-specific date functions query_oracle_dev("SELECT employee_id, hire_date FROM employees WHERE hire_date >= TRUNC(SYSDATE, 'YEAR')")

-- Oracle sequence operations execute_oracle_dev("CREATE SEQUENCE emp_seq START WITH 1000 INCREMENT BY 1") query_oracle_dev("SELECT emp_seq.NEXTVAL FROM DUAL")

-- Oracle-specific data types query_oracle_dev("SELECT order_id, TO_CHAR(order_date, 'YYYY-MM-DD HH24:MI:SS') FROM orders")

-- Get schema metadata from Oracle data dictionary query_oracle_dev("SELECT column_name, data_type, nullable FROM user_tab_columns WHERE table_name = 'EMPLOYEES'")

-- Use Oracle analytic functions query_oracle_dev("SELECT employee_id, salary, RANK() OVER (ORDER BY salary DESC) as salary_rank FROM employees")

## Troubleshooting

Common Issues
Connection Failures: Verify network connectivity and database credentials
Permission Errors: Ensure the database user has appropriate permissions
Timeout Issues: Check the query_timeout setting in your configuration
Logs
Enable verbose logging for troubleshooting:

## Testing

Running Tests
The project includes comprehensive unit and integration tests for all supported databases.
Unit Tests
Run unit tests (no database required):

or

#### Integration Tests

Integration tests require running database instances. We provide Docker Compose configurations for easy setup.
Test All Databases:

Start test databases

Run all integration tests

Stop test databases

Test Oracle Database:

Start Oracle test environment

Run Oracle tests

or manually

Stop Oracle test environment

Full cleanup (removes volumes)

Test TimescaleDB:

Start TimescaleDB test environment

Run TimescaleDB tests

Stop TimescaleDB test environment

#### Regression Tests
Run comprehensive regression tests across all database types:

Ensure all test databases are running

Run regression tests

Run connection pooling tests

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'feat: add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

1. All unit tests pass: go test -short ./...
2. Integration tests pass for affected databases
3. Code follows the project's style guidelines: golangci-lint run ./...`
4. New features include appropriate test coverage

License

This project is licensed under the MIT License - see the LICENSE file for details.