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eea-climate-data-mcp

eea-climate-data-mcp

by bezilaszlo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

preview_rows

Preview a small sample of rows from any EEA climate data table, including provenance details, to quickly verify data structure and content before running full queries.

Instructions

Preview a small bounded set of rows with provenance.

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": "preview_rows"
  }
}

Input Schema

NameRequiredDescriptionDefault
tableYes
versionYes
databaseYes
max_rowsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the row set is 'small' and 'bounded,' implying a limit, and that provenance is included. However, it does not explicitly state that the operation is read-only, safe, or how limits are enforced, leaving room for ambiguity.

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

Conciseness3/5

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

The description is a single sentence with no wasted words, which is positive. However, it is so brief that it under-specifies key aspects, so the structure is 'short' rather than 'effectively concise.' It earns a middle score.

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

Completeness2/5

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

Given the tool has an output schema, return values are partially covered elsewhere. But the description omits essential context: what 'provenance' entails, how max_rows interacts with the bound, what the database/version/table refer to, and when this tool is preferred. This is inadequate for a 4-parameter exploratory tool.

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

Parameters1/5

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

Schema description coverage is 0%, and the description adds no explanation of the parameters (database, version, table, max_rows). The agent is left to infer meaning solely from parameter names, which is insufficient and does not compensate for the missing schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Preview') and resource ('rows') and adds 'a small bounded set' and 'with provenance,' distinguishing it from broadly querying or fetching full tables. It does not explicitly mention sibling tools, but the phrasing conveys a scoped, safe-read intent.

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?

No usage guidance is provided. The description does not state when to use this tool versus alternatives like query_sql, list_distinct_values, or get_provenance, nor does it specify when a larger query would be more appropriate.

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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