Skip to main content
Glama

Arcgis Pflugerville

by io.github.pipeworx-io

Send Pipeworx Feedback

pipeworx_feedback

Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a claim_token; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNobug = something broke or returned wrong data. feature = a new tool or capability you wish existed. data_gap = data Pipeworx does not currently expose. praise = positive note. other = anything else.
contextNoOptional structured context: which tool, pack, or vertical this relates to.
messageNoYour feedback in plain text. Be specific (which tool, what error, what data was missing). 1-2 sentences typical, 2000 chars max.
claim_tokenNoRead the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / properties / claim_token
      Added value: +{
+  "description": "Read the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.",
+  "type": "string"
+}
    • removedInput schema / required
      Removed value: -[
-  "type",
-  "message"
-]
  2. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only provide generic false hints, so the description carries the full burden and does so richly: it discloses rate limiting (5 per identifier per day), that it is free and doesn't count against quota, anonymous filing returns a claim_token, and team reads digests daily. No contradiction with annotations.

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 somewhat long but every sentence earns its place: purpose, scope, exclusion, mechanics, limits. It is front-loaded with the core action and structured logically, with no filler or redundant restating of the title or schema.

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

Completeness5/5

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

For a tool with 4 params, a nested context object, and no output schema, the description is complete. It covers invocation, return token behavior, rate limits, and scope boundaries. There are no notable gaps in understanding how or when to use the tool.

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

Parameters4/5

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 adds meaningful semantics for claim_token (how to pass it back later to read resolution status) and advises 'Describe the issue in terms of Pipeworx tools/packs,' but it doesn't elaborate on individual parameters beyond what the schema already states.

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 opens with a specific verb+resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It clearly distinguishes from sibling tools by scoping exclusively to Pipeworx feedback categories (bug, feature, data_gap, praise) and explicitly excludes tools from other MCP servers.

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

Usage Guidelines5/5

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

Provides explicit when-to-use guidance for each feedback type and a strong when-not-to-use exclusion: 'if the tool came from a different MCP server... file it with that server instead.' Also instructs not to paste end-user prompts and explains how to use claim_token to check resolution.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Arcgis Pflugerville toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation2/5

The tool set contains multiple overlapping tools for data querying (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, suggest_questions) and prediction market analysis (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread), making it difficult for an agent to distinguish which tool to use. The GIS-specific tools are few and could be confused with general data tools.

Naming Consistency2/5

Tool names follow no consistent pattern: some use verb_noun or noun_verb (ask_pipeworx, compare_entities, search_datasets), while others are longer phrases (generate_llms_txt, scan_competitor_ai_presence, polymarket_kalshi_spread). Mixed conventions and lack of uniformity reduce predictability.

Tool Count2/5

With 34 tools, the count is high for a server ostensibly focused on ArcGIS Pflugerville. Many tools are unrelated to GIS (e.g., prediction market tools, general Pipeworx utilities), making the tool surface feel bloated and poorly scoped.

Completeness2/5

For an ArcGIS server, the coverage is minimal: only three tools (search_datasets, layer_info, query_layer) directly support GIS operations. Missing typical GIS capabilities like geocoding, spatial analysis, or editing. The inclusion of many non-GIS tools does not compensate for the lack of depth in the core domain.

Resources