pifini

Get place details + reviews

get_place

Read-onlyIdempotent

Full details for one place by slug, including its most recent published reviews if any exist. listing_type distinguishes a curated entry from an unreviewed directory listing (see search_places) — recent_reviews is often an empty array, which means no reviews yet, not a low-quality place. Use the slug from search_places.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`slug`	Yes	Place slug from search_places

Output Schema

TableJSON Schema

Name	Required	Description	Default
`url`	No
`city`	No
`name`	No
`slug`	No
`type`	No
`address`	No
`country`	No
`summary`	No
`website`	No
`category`	No
`avg_rating`	No
`price_tier`	No
`description`	No
`is_verified`	No
`is_sponsored`	No
`listing_type`	No
`review_count`	No
`recent_reviews`	No

Schema Changelog

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

Changed1 schema field changedAug 5, 2026

addedOutput schema / properties / recent_reviews / items

Added value: +{
+  "properties": {
+    "body": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "date": {
+      "type": "string"
+    },
+    "rating": {
+      "type": "number"
+    },
+    "title": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "verified_attendee": {
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "rating",
+    "verified_attendee",
+    "date"
+  ],
+  "type": "object"
+}

Changed1 schema field changedJul 28, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "address": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "avg_rating": {
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "category": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "city": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "country": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "description": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "is_sponsored": {
+      "type": "boolean"
+    },
+    "is_verified": {
+      "type": "boolean"
+    },
+    "listing_type": {
+      "enum": [
+        "curated",
+        "directory"
+      ],
+      "type": "string"
+    },
+    "name": {
+      "type": "string"
+    },
+    "price_tier": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "recent_reviews": {
+      "type": "array"
+    },
+    "review_count": {
+      "type": "number"
+    },
+    "slug": {
+      "type": "string"
+    },
+    "summary": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "type": {
+      "type": "string"
+    },
+    "url": {
+      "type": "string"
+    },
+    "website": {
+      "type": [
+        "string",
+        "null"
+      ]
+    }
+  },
+  "type": "object"
+}

First observedJul 2, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Beyond the readOnly and idempotent annotations, the description adds semantic context: recent_reviews being an empty array means no reviews yet (not low quality), and listing_type distinguishes curated vs directory entries. This helps interpret results.

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

Conciseness4/5

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

The description is compact and front-loaded, with the main purpose in the first sentence and useful interpretive context in the second. It is efficient, though the phrase 'Use the slug from search_places' somewhat duplicates schema info.

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?

For a simple single-parameter, read-only tool, the description provides adequate context: what the tool does, where the slug comes from, and key behavioral traits of the response (reviews and listing_type). The presence of an output schema covers the need to enumerate all fields.

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?

The only parameter, slug, is fully described in the schema as 'Place slug from search_places'. The description just repeats this instruction without adding new format details, so it remains at the schema-coverage baseline.

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 it retrieves full details for a single place by slug, including reviews. This distinguishes it from siblings like search_places and get_event by focusing on slug-based individual lookup.

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?

It instructs to use the slug from search_places, establishing a workflow and referencing the alternative tool for context. However, it does not explicitly say when not to use this tool (e.g., for filtered or searched lists), leaving some room for inference.

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

A4.4/5.0

Disambiguation5/5

Each tool has a distinct purpose: search vs. get by slug for both events and places, plus a category lookup and a checkout action. The clear separation between search and detail retrieval prevents confusion. No two tools appear to overlap in functionality.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case: create_, get_, list_, search_. The naming is uniform and predictable, making it easy to infer what each tool does from its name.

Tool Count5/5

With 6 tools, the server is well-scoped for its purpose of exploring events and places. Each tool covers a distinct aspect—search, detail retrieval, category lookup, and ticket checkout—without redundancy or bloat. This is within the ideal range for a focused MCP server.

Completeness4/5

The tool set covers the main workflows: discovering events and places, viewing details, and purchasing tickets. A minor gap is the lack of a category taxonomy for events, as list_categories is specific to places, but event categories are returned in search results and can be used ad hoc. Overall, the surface is functionally complete for consumers.

Resources

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