Schema | pg-semantic-mcp

pg-semantic-mcp

Describes the environment variables required to run the server.

Name	Required	Description	Default
`LLM_MODEL`	No	LLM model name	gpt-4o-mini
`LLM_API_KEY`	No	Required for search_schema
`DATABASE_URL`	Yes	PostgreSQL connection string
`LLM_BASE_URL`	No	OpenAI-compatible endpoint	https://api.openai.com/v1
`CACHE_SCHEMAS`	No	Comma-separated schema names to cache	all
`SEMANTIC_FILE`	No	Path to your semantic layer markdown
`SAMPLE_DATA_LIMIT`	No	Default row count for sample_data	5
`CACHE_REFRESH_MINUTES`	No	Background cache refresh interval	30

Features and capabilities supported by this server

Capability	Details
`tools`	{ "listChanged": true }
`logging`	{}
`prompts`	{ "listChanged": false }
`resources`	{ "subscribe": false, "listChanged": false }
`extensions`	{ "io.modelcontextprotocol/ui": {} }
`experimental`	{}

Functions exposed to the LLM to take actions

Name	Description
list_tablesA	List all tables in the database with their comments.
describe_tableA	Return column metadata for a table.
sample_dataA	Return sample rows from a table.
search_schemaA	Semantically search tables and columns by keyword using LLM. Combines the in-memory schema cache and the semantic layer markdown (if configured) into a prompt, then calls the configured LLM to find relevant tables and columns.

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/chncaesar/pg-semantic-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server