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MCPg - Production-grade PostgreSQL MCP Server

MCPg - Production-grade PostgreSQL MCP Server

by devopam
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Generate Ent schemas

generate_ent_schemas
Read-only

Generates Ent (Go) schema struct files from a PostgreSQL schema, one .go file per table with fields, FK edges, and enum values, returning {filename: source} so an agent can write them.

Instructions

Read a PostgreSQL schema and emit Ent (Go) Schema struct files — one .go file per table. Each file exports a struct that lists field.X(...) calls for every column, edge.To(...) for single-column intra-schema FKs, and field.Enum().Values() for enum-typed columns. Composite FKs are a documented v1 gap. Returns a JSON object {filename: source} so the agent can write each file. Schema/table/column names must be plain identifiers ([A-Za-z_][A-Za-z0-9_]*); delimited names (hyphens, spaces, mixed-case-only) are not supported here because they become source identifiers in generated code — use SQL tools (export_table, dump_database) for those objects. See docs/identifier-policy.md.

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": {
      "schema": "<schema>"
    },
    "name": "generate_ent_schemas"
  }
}

Input Schema

NameRequiredDescriptionDefault
schemaYes
databaseNoOptional: a database id from list_databases, to target a configured secondary (read-only) database; omit for the primary. Database names that are not configured ids are rejected.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.8.4
    • changedInput schema / properties / database / description
      Previous value: -"Optional: target a configured secondary (read-only) database by name; omit for the primary. Call list_databases to see the configured ids."New value: +"Optional: a database id from list_databases, to target a configured secondary (read-only) database; omit for the primary. Database names that are not configured ids are rejected."
  2. First observedv0.6.8

TDQS

A4.4/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true and openWorldHint=false, and the description is fully consistent with a read-only inspection. It goes well beyond them: documents the v1 limitation (composite FKs unsupported), states the return shape ({filename: source}) and the agent's implied next action (write each file), and flags the identifier-name constraint.

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?

Front-loaded with verb and output artifact, then limitations, then constraints. Dense and mostly waste-free; the identifier policy paragraph is slightly repetitive in restating the same constraint twice and pointing to external docs.

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?

An output schema exists, yet the description still explains the return shape and that one file is produced per table. For a code generator with a documented v1 gap and naming constraint, an agent has everything needed to call it and handle the result.

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 50%: the database parameter is documented in the schema, but the required 'schema' parameter has no schema description. The prose 'Read a PostgreSQL schema' loosely implies what schema means, but no details are added about qualification, search_path behavior, or defaults.

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?

Names a specific verb and output artifact: read a PostgreSQL schema and emit Ent (Go) Schema struct files, one .go file per table. The framework qualifier ('Ent') separates it from the sibling generators (generate_prisma_schema, generate_drizzle_schema, generate_ecto_schemas) and the description even previews the emitted constructs (field.X, edge.To, field.Enum().Values()).

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?

Explicitly states the negative case: delimited names (hyphens, spaces, mixed-case-only) are unsupported and should go to export_table or dump_database instead, with the reason given (they become source identifiers). No explicit guidance on choosing among the other schema generators, but the framework naming makes the selection unambiguous.

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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