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Glama
lagaam-ai

Lagaam

Official
by lagaam-ai
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Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
TRINO_HOSTNoTrino coordinator host.localhost
TRINO_PORTNoTrino coordinator port.8080
TRINO_USERNoTrino user.lagaam
LAGAAM_ENGINENoSet to pinot to use the native Pinot adapter.trino
LAGAAM_MAX_ROWSNoScanned-row estimate budget per query.
LAGAAM_AUDIT_LOGNoAudit JSONL file path.stderr
LAGAAM_AGENT_NAMENoIdentity stamped on the audit trail.anonymous
LAGAAM_METADATA_TTLNoMetadata cache TTL, seconds.300
LAGAAM_QUERY_TIMEOUTNoWall-clock seconds per query.300
LAGAAM_ALLOWED_TABLESNoComma list of catalog.schema.table grants. Required unless LAGAAM_ALLOW_ALL_TABLES is set to true.
LAGAAM_MAX_SCAN_BYTESNoScan-bytes budget per query, pre-execution.53687091200
LAGAAM_ALLOW_ALL_TABLESNoSet to true to run with no grant at all.
LAGAAM_MAX_RETURNED_ROWSNoRows returned to the agent per query; max 100000.1000
LAGAAM_MAX_INTERMEDIATE_ROWSNoRows the engine would build at its widest step.50000000

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
list_catalogsA

List every catalog, schema, and table you are allowed to query.

Call this first to ground yourself before describing tables or writing SQL — table names you have not seen here are guesses.

describe_tableB

Get the exact columns and types of one table.

Always describe a table before querying it; column names you have not seen here are guesses.

query_dataA

Run a read-only SELECT and get the rows back.

    Write a single SELECT in the engine's dialect. The query is checked
    for safety, priced against your budget, and executed with a row cap —
    so name the columns you need (no SELECT *), and add WHERE filters to
    keep the scan small. If it is rejected, the message says what to fix.
    Describe the tables first so column and table names are exact.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.1/5.0

Scored across 3 tools

Disambiguation5/5

The three tools map to clearly distinct stages of a data workflow: discovery (list_catalogs), schema introspection (describe_table), and execution (query_data). There is no overlap in purpose, and the descriptions actively steer the agent between them.

Naming Consistency5/5

All three names follow the same snake_case verb_noun pattern (list_catalogs, describe_table, query_data). The convention is predictable and self-explanatory.

Tool Count5/5

Three tools is exactly right for a read-only SQL access server — each earns its place with no redundancy. Adding more would only fragment the discover-describe-query workflow.

Completeness4/5

The surface fully covers the read-only lifecycle: explore, inspect schema, then query. Write operations are absent, but that is a deliberate scope choice rather than a gap, leaving only minor omissions such as metadata or sample-value helpers.

Maintenance

ActivityActive
ResponsivenessUnresponsive

Resources