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Elekto MCP for SQL Server

Elekto MCP for SQL Server

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Schema summary

get_schema_summary
Read-onlyIdempotent

Summarize each database schema with table, view, procedure, and function counts plus approximate rows and estimated data/index size, so you can see where a database's weight lies before refactoring.

Instructions

Summarizes each schema of a database: counts of tables, views, procedures and functions, approximate rows and estimated data and index size. Use it to see where a database's weight lies before exploring or planning a refactoring; for whole-database totals use get_database_overview, and for the tables of one schema use list_tables.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "database": "<database>"
    },
    "name": "get_schema_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
schemaNoFilter by schema name. Empty means every schema. Example: 'Feeder'
databaseYesName of the database as registered in the configuration.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is fully covered. The description adds useful content-level detail about what the summary contains (row estimates, index/data size), which matters since there is no output schema, but it says nothing about cost, limits, or behavior on unregistered/large databases. With annotations carrying the safety burden, a 3 is appropriate.

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: the first delivers the payload contents, the second front-loads the routing decision before naming alternatives. Every clause earns its place.

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

Completeness5/5

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

For a read-only aggregate tool with no output schema, the description supplies the return contents, the intended planning use case, and disambiguation from the two nearest siblings. Nothing an agent needs in order to call it correctly is missing.

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%: both parameters are documented in the schema, including the empty-string default meaning 'every schema' and an example value. The description adds no parameter-level syntax or filtering semantics beyond what the schema already provides, so the baseline 3 applies.

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

Purpose5/5

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

States a specific verb (summarizes) and resource (each schema of a database) and enumerates exactly what is produced: table/view/procedure/function counts, approximate rows, and estimated data/index size. It explicitly distinguishes itself from get_database_overview and list_tables, so an agent can place it among 20 siblings without opening the schema.

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

Usage Guidelines5/5

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

Gives an explicit use case ('before exploring or planning a refactoring') and names two alternatives with the conditions that select them: whole-database totals -> get_database_overview, tables of one schema -> list_tables. Nothing is left to inference.

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

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