Skip to main content
Glama
Auto Ontology MCP

Auto Ontology MCP

by gogoymh

Add Datasource

add_datasource
Idempotent

Register a read-only database connection and scan its schema by default to build an ontology-aware semantic layer. Provide a connection URL; credentials are never invented.

Instructions

Register a database (connections are always read-only) and, by default, scan it. Use only when the user gives you a connection URL; never invent credentials.

Input Schema

NameRequiredDescriptionDefault
urlYesSQLAlchemy URL, e.g. sqlite:////abs/path/file.db, postgresql+psycopg://user:pass@host:5432/db, mysql+pymysql://user:pass@host/db, duckdb:///file.duckdb.
nameYesShort name, e.g. 'shop'.
scanNoScan the schema right away.
schemasNoSchemas to include (default: all non-system schemas).
descriptionNoWhat this database holds.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes meaningfully beyond annotations: it clarifies that the stored connection is always read-only (reconciling the readOnlyHint=false write semantics), discloses the default schema scan side effect, and warns against fabricating credentials. Missing is what happens on duplicate registration or how long a scan of a large database takes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, zero filler, with the core action and the default scan behavior front-loaded before the usage restriction. Every clause carries information an agent needs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

A mutation tool with annotations, a full output schema, and complete parameter docs — the description covers the behavior an agent must know to call it safely. Only edge cases like duplicate names or long-running scans are absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so each of the five parameters is already fully documented, including URL syntax examples and the default-true scan flag. The description only reiterates the URL requirement and the scan default, adding no semantics beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb and resource: 'Register a database' with the added default behavior of scanning it, plus a note that the resulting connection is read-only. That distinguishes it reasonably from scan_datasource, though the sibling is never named explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Use only when the user gives you a connection URL; never invent credentials' is a clear inclusion condition plus a hard exclusion. It stops short of naming alternatives or stating what to do if the datasource already exists, deferring that to the idempotent hint.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.