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Fibery MCP Server (deprecated)

Fibery MCP Server (deprecated)

Official
by Fibery-inc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

describe_database

Retrieve all fields and their data types from a specified Fibery database and its related databases to understand data structure.

Instructions

Get list of all fields (in format of 'Title [name]: type') in the selected Fibery database and for all related databases.

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_name": "<database_name>"
    },
    "name": "describe_database"
  }
}

Input Schema

NameRequiredDescriptionDefault
database_nameYesDatabase name as defined in Fibery schema

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.0

TDQS

A3.5/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden but only states what the tool returns, not behavioral traits like whether it's read-only, requires permissions, has rate limits, or error handling. It doesn't disclose if it's safe or has side effects.

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?

The description is a single, efficient sentence that front-loads the purpose and includes key details like output format and scope. There's zero wasted verbiage, making it highly concise and well-structured.

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

Completeness3/5

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

For a simple read operation with one parameter and no output schema, the description is adequate but lacks context on permissions, errors, or return structure beyond format hints. It doesn't fully compensate for missing annotations, leaving behavioral gaps.

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 description coverage is 100%, so the schema already documents the single parameter 'database_name'. The description adds no additional meaning beyond implying it selects a database, matching the baseline for high schema coverage.

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 clearly states the specific action ('Get list of all fields') and the resource ('selected Fibery database and for all related databases'), with precise output format details. It distinguishes itself from siblings like 'list_databases' (which lists databases) and 'query_database' (which queries data).

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

Usage Guidelines3/5

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

The description implies usage when needing field metadata for a specific database and its relations, but doesn't explicitly state when to use this vs. alternatives like 'list_databases' or 'query_database'. No exclusions or prerequisites are mentioned.

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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