Skip to main content
Glama

building-intelligence

by com.lucidrents
OverviewDiscussionsAdmin

Search buildings

search_buildings
Read-onlyIdempotent

Search LucidRents for apartment buildings by address, building name, or partial address. Covers ~2M buildings in New York City, Los Angeles, and Chicago with public-record data: housing violations, 311 complaints, tenant reviews, rents, and building scores. Returns up to 10 matches with each building's slug (needed for get_building_report / get_review_summary) and its lucidrents.com report URL. Start here when the user gives an address.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoOptional city filter. Omit to search all covered cities.
queryYesAddress or building name to search, e.g. "48-04 48th Ave" or "350 Park Ave"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesCity searched, or "all"
moreYesWhat the linked page adds beyond this payload
queryYes
resultsYesUp to 10 matches, best first
data_as_ofYesISO date of the data snapshot
result_countYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / city / enum
      Previous value: -[
-  "nyc",
-  "los-angeles",
-  "chicago"
-]New value: +[
+  "nyc"
+]
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "city": {
+      "description": "City searched, or \"all\"",
+      "type": "string"
+    },
+    "data_as_of": {
+      "description": "ISO date of the data snapshot",
+      "type": "string"
+    },
+    "more": {
+      "description": "What the linked page adds beyond this payload",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "query": {
+      "type": "string"
+    },
+    "result_count": {
+      "type": "number"
+    },
+    "results": {
+      "description": "Up to 10 matches, best first",
+      "items": {
+        "additionalProperties": {},
+        "properties": {
+          "address": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "borough": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "city": {
+            "type": "string"
+          },
+          "grade": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "description": "Letter grade derived from the score (\"A+\" through \"F\", \"—\" when unscored)"
+          },
+          "review_count": {
+            "type": "number"
+          },
+          "score": {
+            "anyOf": [
+              {
+                "type": "number"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "description": "LucidIQ score, 0-100"
+          },
+          "slug": {
+            "description": "Building slug — pass to get_building_report / get_review_summary",
+            "type": "string"
+          },
+          "url": {
+            "description": "Canonical lucidrents.com page URL (UTM-tagged)",
+            "type": "string"
+          },
+          "violation_count": {
+            "type": "number"
+          }
+        },
+        "required": [
+          "slug",
+          "city",
+          "violation_count",
+          "review_count",
+          "url"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "query",
+    "city",
+    "result_count",
+    "results",
+    "data_as_of",
+    "more"
+  ],
+  "type": "object"
+}
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, and non-destructive behavior, so the description adds value by disclosing the match cap (10), city scope, data sources, and output components (slug + report URL). This goes beyond the structured metadata without contradicting 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?

The description is three sentences, front-loads the core purpose, and every sentence adds useful information: coverage, data types, return contents, and when to use. No wasted words or redundant restating of the title.

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?

Given the output schema exists and annotations cover safety, the description provides enough operational context: city coverage, public-record data categories, result limit, output purpose (slug for downstream tools), and a usage cue. This is complete for a read-only 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% and the schema already documents query and city with examples and constraints. The description reinforces that query can be an address or building name and that city is optional, but it doesn't add symbolic meaning beyond the schema. Baseline 3 applies.

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 names the verb + resource ('Search LucidRents for apartment buildings') and specifies the search dimensions (address, building name, partial address). It also differentiates this from siblings by noting it produces the slug needed for downstream report tools.

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 says 'Start here when the user gives an address,' which is explicit when-to-use guidance. It also explains that the returned slug is needed for get_building_report / get_review_summary, establishing the tool's place in the workflow. It doesn't list explicit when-not-to-use scenarios, but the context is clear enough.

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

All building-intelligence toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources