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eea-climate-data-mcp

eea-climate-data-mcp

by bezilaszlo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

describe_table

Provides schema, grain, keys, joins, reporting cycle, and caveats for any table in the EEA climate data server, helping you understand data structure before querying.

Instructions

Describe schema, grain, keys, joins, reporting cycle, and caveats.

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>",
      "version": "<version>",
      "table": "<table>"
    },
    "name": "describe_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
tableYes
versionYes
databaseYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only lists content categories and does not state whether the operation is read-only, whether permissions are required, or what side effects might occur. The verb 'describe' weakly implies non-mutation, but this is not explicit.

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, well-structured sentence that front-loads the key components. Every word contributes directly to the tool's purpose, with no wasted filler.

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?

Though an output schema exists and the tool is a simple describe operation, the absence of parameter documentation and usage guidance leaves gaps. The description is minimally adequate for basic selection but lacks depth needed for full contextual understanding.

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

Parameters2/5

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

Input schema has 0% description coverage, and the tool description does not explain the roles of database, version, or table parameters. The tool name implies 'table' is the focus, but no additional meaning is given beyond the parameter names themselves.

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 the specific verb 'Describe' and clearly enumerates the scope: schema, grain, keys, joins, reporting cycle, and caveats. This distinguishes it from sibling tools like list_tables or preview_rows, which serve different purposes.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention conditions, exclusions, or compare with sibling tools such as list_tables or search_tables.

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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