Skip to main content
Glama

Arcgis Tallahassee

by io.github.pipeworx-io

Scan Competitor AI Presence

scan_competitor_ai_presence
Read-onlyIdempotent

Compare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our competitors?". Returns ranked list with score, confidence, signal density per entity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsNoWhich models to probe. Supported: "workers-ai" (free default), "anthropic" (requires _apiKey). Omit for just workers-ai.
_apiKeyNoOptional Anthropic API key — only if "anthropic" is in models. Passed to api.anthropic.com per probe.
contextNoOptional shared context applied to every probe (e.g. "B2B SaaS", "Boston restaurant"). Disambiguates common names.
entitiesYesArray of 2-8 entities to compare (brand/business/product names). First entry treated as the "subject" for narrative; rest are competitors.

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already provide readOnly, idempotent, and non-destructive hints. The description adds that it internally uses ai_visibility_check for each entity and returns a ranked list with scores, confidence, and signal density, which is valuable beyond 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?

Three sentences: first states purpose, second explains mechanism and example, third describes output. No redundant information, efficiently 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?

No output schema exists, but description specifies return structure (ranked list with score, confidence, signal density). Also mentions entity count constraint (2-8). Adequate for understanding the tool's functionality.

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 3. The description adds meaning: 'First entry treated as the subject for narrative', explains context parameter, and the relationship between models and _apiKey, thus adding value beyond schema.

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?

Specific verb 'Compare AI visibility' with resource 'multiple entities', and distinguishes from siblings like ai_visibility_check (single entity) and compare_entities (general) by detailing the ranking and scoring behavior.

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?

Explicitly suggests use for 'competitive AI-marketing audits' with an example question, providing clear context. Does not explicitly state when not to use or list alternatives, but the purpose is well-defined.

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

All Arcgis Tallahassee 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

A3.8/5.0
Disambiguation2/5

Multiple tools are near-duplicates or strongly overlapping: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are only mode/version variants, and discover_tools overlaps with suggest_questions, ai_visibility_check with scan_competitor_ai_presence, and the Polymarket tools with each other. An agent would frequently need a deep read of the descriptions to know which one is truly appropriate.

Naming Consistency4/5

The naming is almost entirely snake_case and mostly follows a verb_noun or domain_noun pattern, e.g. query_layer, list_subscriptions, resolve_entity, compare_entities. Minor deviations like entity_profile, pipeworx_feedback, and polymarket_arbitrage are noun-first, but the overall pattern is still recognizable and predictable.

Tool Count2/5

34 tools for a server branded 'Arcgis Tallahassee' is far too many, especially since only a handful of them are GIS-related. The rest constitute a large general-purpose Pipeworx data platform, which at this tool count becomes unwieldy and will increase an agent's selection failure rate.

Completeness3/5

The core read-only GIS flow is covered (search_datasets → layer_info → query_layer), and the Pipeworx side is broad. However, there are notable gaps: no ArcGIS service management, no layer/feature editing, no spatial operations, and no deeper GIS functions. Because the server's stated purpose is ArcGIS-focused, the overall surface is only partially complete relative to that domain.

Resources