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Data Seattle

by io.github.pipeworx-io

Seattle Datasets

seattle_datasets
Read-onlyIdempotent

Search the Seattle open-data catalogue (data.seattle.gov) for datasets by keyword. Returns dataset names, descriptions, and Socrata resource ids to use with seattle_query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax datasets (1-100, default 20).
queryNoKeyword(s), e.g. "parks", "transit", "budget".
offsetNoOffset for paging.
_apiKeyNoOptional — your own Socrata app token for higher rate limits. Omit to use the keyless endpoint.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-data-seattle-api-key",
+    "query": "parks"
+  },
+  {
+    "_apiKey": "your-data-seattle-api-key",
+    "limit": 10,
+    "query": "transit budget"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare read-only, open-world, and idempotent behavior. The description adds value by specifying the return format (dataset names, descriptions, resource ids) and the intended follow-up tool. This goes beyond annotations without contradiction.

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 two sentences: first states the action and resource, second states the return type and usage. Every sentence provides unique information, no fluff, and the key information is front-loaded.

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?

With no output schema, the description adequately explains return values (names, descriptions, resource ids). It also mentions the optional API key indirectly via schema. It could mention pagination behavior or offset parameter, but the offset parameter itself hints at that. Overall, it's sufficient for a search tool.

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 coverage is 100%, so baseline is 3. The description does not add new parameter details beyond the schema, but it provides context for how parameters like 'query' and 'limit' are used in the search. The examples in schema also help, but the description itself is not essential for parameter understanding.

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 verb 'Search', the resource 'Seattle open-data catalogue (data.seattle.gov)', and what is returned. It distinguishes itself from the sibling 'seattle_query' by noting the output is resource ids for use with that tool.

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

Usage Guidelines4/5

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

The description provides clear context by stating it returns Socrata resource ids to use with 'seattle_query', implying a workflow. However, it does not explicitly mention when to avoid this tool or provide alternatives for similar tasks like browsing recent datasets (seattle_recent).

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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TDQS

A4.1/5.0
Disambiguation3/5

Many tools have distinct purposes, but the ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and the prediction market tools (bet_research, polymarket_edges, polymarket_arbitrage) can cause confusion due to overlapping functionality. Some tools like 'seattle_recent' are vague.

Naming Consistency4/5

Most tools follow a consistent verb_noun or noun_verb pattern (e.g., validate_claim, resolve_entity). However, a few like 'seattle_recent' and 'pipeworx_trending' deviate slightly, and 'recent_alerts' mixes noun_verb.

Tool Count2/5

34 tools is excessive for a single server, covering data retrieval, prediction markets, Seattle data, memory, subscriptions, and utility. The broad scope feels bloated and overwhelming, making it hard for agents to find the right tool.

Completeness4/5

The server covers a wide array of domains with good depth in data retrieval and prediction markets. Minor gaps exist (e.g., Seattle tools limited to four datasets, no other city data), but overall it addresses most use cases its tools suggest.

Resources