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socrata-mcp

socrata-mcp

by jcscocca
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

sample

Fetch the first rows of a Socrata dataset to preview real values. Useful for quick data inspection before full analysis.

Instructions

Fetch the first n rows of a dataset (n capped at 100).

Args: domain: Portal hostname, e.g. "data.seattle.gov". dataset_id: Socrata 4x4 id, e.g. "tazs-3rd5". n: Number of rows (default 10, max 100).

Returns: {rows, row_count, note}. Rows are in :id order — a peek at real values, not a random sample.

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": {
      "domain": "<domain>",
      "dataset_id": "<dataset_id>"
    },
    "name": "sample"
  }
}

Input Schema

NameRequiredDescriptionDefault
nNo
domainYes
dataset_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Given no annotations, description discloses key behaviors: max rows, ordering, return shape, and that result is not a random sample. Lacks mention of read-only nature, but fetch implies it.

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?

Single-line summary, structured Args and Returns sections, no redundant information. Front-loaded and efficient.

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?

Covers main concerns for a simple fetch tool: parameter details, return shape, ordering, cap. Sibling tool differentiation absent but not critical for completeness here.

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

Parameters5/5

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

Each parameter is explained with examples and constraints (domain format, dataset id format, default/max for n), fully compensating for 0% schema description 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?

Clearly states verb 'fetch', resource 'first n rows of a dataset', and constraint 'capped at 100'. Distinguishes from random sample by noting rows are in id order.

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?

Implies usage for a quick peek via return description, but does not explicitly contrast with sibling tools like 'query' or 'get_dataset'.

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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