Actian MCP Server for Analytics Engine¶

Connect the MCP-compatible client to the Actian Analytics Engine using the Actian MCP Server. This setup allows you to explore schema metadata and execute read-only SQL queries through a standard interface. The MCP Server for Analytics Engine bridges the gap between the MCP client and the Actian database. The server manages connection pooling, response formatting, and schema discovery automatically, allowing you to focus on the data.

Capabilities¶

The Actian Analytics Engine MCP Server supports the following operations:

Action	Description
Execute SQL queries	Execute read-only SQL against the database
List tables and views	Discover available objects in the schema
Inspect table structure	Retrieve column definitions and types
Read schema metadata	Explore database-level metadata
List functions and procedures	View available user-defined functions and procedures

Prerequisites¶

Before starting the server, ensure the following requirements are met:

Container Engine: Docker installed and running on the host machine.
Database credentials: Valid access for the Analytics Engine database.
Security files (optional): TLS certificate and key files for secure deployments.
OIDC provider (optional): Required if you are using OAuth authentication.

Configuration¶

The server runs as a Docker container. To configure the server, mount the (conf.json) file to the container at /app/conf.json.

Create the Configuration File¶

Create a file named conf.json in your working directory using the following structure:

{
  "driver": "<odbc_driver>",
  "server": "<database_host>",
  "database": "<database_name>",
  "max_connections": "<max_concurrent_connections>",
  "max_rows": "<max_rows_per_query_response>",
  "host": "<mcp_server_host>",
  "port": "<mcp_server_port>",
  "database_user": "<database_user>",
  "database_password": "<database_password>",
  "log_level": "INFO",
  "ssl_certfile": "/app/server.crt",
  "ssl_keyfile": "/app/server.key",
  "oauth": {
    "FASTMCP_SERVER_AUTH_CONFIG_URL": "<oidc_discovery_url>",
    "FASTMCP_SERVER_AUTH_CLIENT_ID": "<client_id>",
    "FASTMCP_SERVER_AUTH_CLIENT_SECRET": "<client_secret>",
    "FASTMCP_SERVER_AUTH_BASE_URL": "<server_base_url>",
    "FASTMCP_SERVER_AUTH_AUDIENCE": "<audience>",
    "user_impersonation": true
  }
}

Configuration Reference¶

Required Fields

Field	Type	Description
`driver`	`string`	ODBC driver name used to connect to Analytics Engine
`server`	`string`	Host or connection target for the Analytics Engine database
`database`	`string`	Name of the database.
`max_connections`	`integer`	Maximum concurrent database connections in the pool
`host`	`string`	Host address that the MCP Server listens to in the container
`port`	`string`	Port that the MCP Server listens to in the container
`database_user`	`string`	Database username
`database_password`	`string`	Database password

Optional fields

Field	Type	Default	Description
`max_rows`	`integer`	`1000`	Maximum number of rows returned per query response. Default is `1000`.
`log_level`	`string`	`INFO`	Server log verbosity. Valid values are `DEBUG`, `INFO`, `WARNING`, `ERROR`, `CRITICAL`.
`ssl_certfile`	`string`	—	Path to the TLS certificate file. Add `/app/server.crt` in the container.
`ssl_keyfile`	`string`	—	Path to the TLS private key file. Add `/app/server.key` in the container.
`oauth`	`object`	—	OAuth configuration block for protected deployments. For more information, see OAuth configuration.

Start the Server¶

Once you have created the conf.json file, start the container and mount the configuration file:

docker run -d \
  -v $(pwd)/conf.json:/app/conf.json:ro \
  actian/analytics-engine-mcp-server:1.0.0

Important

The container reads its configuration from /app/conf.json. Do not change the mount target path.

After the container starts, connect the MCP client to the server endpoint using the host and port specified in conf.json.

Usage¶

Once connected, the MCP client automatically discovers the server capabilities. You can perform the following tasks:

Inspect before querying: List tables and review structure before writing SQL.
Run a query: Execute a read-only SQL statement and receive formatted results.
Explore functions: Look up available user-defined functions and stored procedures.
Summarize results: Ask the client to interpret or summarize query output.

Next Steps¶

Tools
Learn more about the Analytics Engine tools used by the MCP Server.
Resources
Explore the resource types available through the server.
Prompts
Use the built-in prompt templates for common workflows.