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SEAF MCP Server

SEAF MCP Server

by aberkromb
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Структура раздела

describe_section
Read-onlyIdempotent

Retrieves structure for one section—attributes, relation fields, and ID examples—without sample data. Use it before querying entities or writing JSONata.

Instructions

Когда вызывать: нужна структура ОДНОГО раздела без образцов — атрибуты с частотой, исходящие/входящие поля-связи, примеры ID. Для образцов данных и нескольких разделов сразу используйте inspect_sections. Дальше: list_entities (выборка по фильтрам) или describe_query_result (разведка перед JSONata).

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": {
      "section": "<section>"
    },
    "name": "describe_section"
  }
}

Input Schema

NameRequiredDescriptionDefault
sectionYesРаздел, например seaf.company.systems

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds value beyond them by disclosing the shape of the response (attribute frequencies, relation fields, ID examples) and its role as a discovery step. It stops short of describing result size, pagination, or cost, which keeps it from a 5.

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?

Three compact, front-loaded clauses: when to call, the contrasting alternative, and follow-on tools. Every sentence carries routing or scope information with no filler.

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?

No output schema exists, so the description must convey return content, and it does at a summary level (attributes with frequency, incoming/outgoing relation fields, ID examples). It is sufficient to decide and call the tool, though the depth and format of those results remain only loosely characterized.

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?

There is a single required parameter and schema coverage is 100%, with the schema itself giving a concrete example ('seaf.company.systems'). The description only implies the single-section constraint ('ОДНОГО раздела') and adds no format or syntax detail, 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?

The description uses a specific verb+resource ('structure of ONE section') and enumerates what it returns: attributes with frequency, outgoing/incoming relation fields, and ID examples. It explicitly distinguishes itself from inspect_sections, so an agent can pick correctly 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?

It opens with an explicit 'when to call' condition ('structure of ONE section without samples') and names the alternative for the contrasting case ('data samples and multiple sections at once -> inspect_sections'). It even chains the likely next tools (list_entities, describe_query_result), which is unusually complete routing guidance.

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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