Elekto MCP for SQL Server

Official

Overview Schema Source Related Servers Discussions Admin

Dependency diagram (DOT)

generate_dependency_dot

Read-onlyIdempotent

Generate a Graphviz DOT diagram of SQL Server database object dependencies, with arrows from tables, views, procedures, and functions to referenced objects.

Instructions

Generates a Graphviz DOT diagram of the dependencies between database objects: an arrow runs from each table, view, procedure or function to the object it depends on, through a foreign key or a reference in its code. Returns the DOT text in 'dot', ready for 'dot -Tsvg', and the same graph as 'nodes' (with node_kind) and 'edges' (with dependency_kind). Use it to draw the graph; for the edges alone use get_dependency_graph, and for what references a single table use get_table_usage. A whole database makes an unreadable diagram, so narrow it with schema. 'visibility' says when references from code are missing for lack of permission.

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": "generate_dependency_dot"
  }
}

Input Schema

Name	Required	Description	Default
`schema`	No	Filter by schema name. Empty means every schema. Example: 'Feeder'
`database`	Yes	Name of the database as registered in the configuration.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 4, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds real context beyond them: the return payload structure ('dot', 'nodes' with node_kind, 'edges' with dependency_kind) and a permission caveat via 'visibility'. The caveat that references from code can be missing for lack of permission is valuable behavioral disclosure that annotations do not carry.

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

Conciseness4/5

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

Three sentences, front-loaded with purpose and edge semantics, then output shape, then alternatives and caveats. Dense but nearly every clause earns its place; the mention of 'visibility' without saying whether it is an input or output field adds slight ambiguity.

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?

No output schema exists, so the description carries the return-value burden and does so by naming the 'dot', 'nodes' and 'edges' fields. Combined with alternatives, the schema-filter caveat and the permission caveat, an agent has everything needed to call and interpret this tool.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3; the description goes further by explaining the practical consequence of the schema filter ('a whole database makes an unreadable diagram, so narrow it with schema'), which gives the agent a reason to set it rather than just its format.

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 and resource ('Generates a Graphviz DOT diagram of the dependencies between database objects') and immediately clarifies the edge semantics (arrow from each object to what it depends on, via FK or code reference). It is clearly distinguishable from the sibling get_dependency_graph, which returns edges only.

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?

Explicitly routes the agent: use this to draw the graph, use get_dependency_graph for edges alone, and get_table_usage for references to a single table. It also warns that a whole-database diagram is unreadable and instructs narrowing with schema, which is actionable when-to-use guidance.

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