Seemor Restaurant Intelligence

Look Up Restaurant

lookup_restaurant

Read-onlyIdempotent

Look up a specific restaurant by its Seemor ID. Returns grade, summary, cuisine, neighborhood, and other details. Use the fields parameter to request richer data (standard or premium; fully analyzed restaurants only, except the quick-read dimension_assessments below). coverage_level 'full' rows carry a letter grade; 'basic' rows are Seemor quick reads: review-analysis bands (grade null, preliminary_band such as 'B-range') with a one-line tldr, graded from review analysis rather than star ratings; With fields 'premium' a quick-read row also carries dimension_assessments for the dimensions the quick read measured (food quality, consistency, noise, service attentiveness, large parties, local vs tourist, value), labelled on the same scale as full analysis but read from fewer reviews, so present them as preliminary. 'none' rows have no analysis yet. Use search_restaurants or find_restaurant first to get restaurant IDs. Use this for a single place the user asks about, not for every result of recommend.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`fields`	No	Response detail level. 'basic' (default): grade, TL;DR, cuisine, price. 'standard': adds narrative summary, occasion fit, menu highlights, cost estimates, dietary info. 'premium': adds dimensional assessments (noise, formality, authenticity, etc.), value assessment, standout strengths/weaknesses, unique selling points.
`restaurant_id`	Yes	Seemor restaurant ID (UUID). Get IDs from search_restaurants results.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	No
`message`	No
`restaurant`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed8 schema fields changedAug 22, 2026
- addedOutput schema / properties / message
```
Added value: +{
+  "type": "string"
+}
```
- addedOutput schema / properties / restaurant / properties / address
```
Added value: +{
+  "type": [
+    "string",
+    "null"
+  ]
+}
```
- addedOutput schema / properties / restaurant / properties / analysis_date
```
Added value: +{
+  "type": [
+    "string",
+    "null"
+  ]
+}
```
- addedOutput schema / properties / restaurant / properties / caveats
```
Added value: +{
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
```
- addedOutput schema / properties / restaurant / properties / city
```
Added value: +{
+  "type": [
+    "string",
+    "null"
+  ]
+}
```
- addedOutput schema / properties / restaurant / properties / coverage_level
```
Added value: +{
+  "enum": [
+    "full",
+    "basic",
+    "none"
+  ],
+  "type": "string"
+}
```
- addedOutput schema / properties / restaurant / properties / preliminary_band
```
Added value: +{
+  "type": [
+    "string",
+    "null"
+  ]
+}
```
- addedOutput schema / properties / restaurant / properties / seemor_url
```
Added value: +{
+  "type": "string"
+}
```
Changed5 schema fields changedAug 22, 2026
- changedOutput schema / properties / restaurant / properties / grade / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
- changedOutput schema / properties / restaurant / properties / grade_label / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
- changedOutput schema / properties / restaurant / properties / neighborhood / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
- changedOutput schema / properties / restaurant / properties / price_level / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
- changedOutput schema / properties / restaurant / properties / tldr / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```

Changed1 schema field changedJul 13, 2026

changedInput schema / properties / fields / description

Previous value: -"Response detail level. 'basic' (default): grade, TL;DR, cuisine, price. 'standard': adds narrative summary, occasion fit, menu highlights, cost estimates, dietary info. 'premium': adds dimensional scores (noise, formality, authenticity, etc.), value assessment, strengths/weaknesses."New value: +"Response detail level. 'basic' (default): grade, TL;DR, cuisine, price. 'standard': adds narrative summary, occasion fit, menu highlights, cost estimates, dietary info. 'premium': adds dimensional assessments (noise, formality, authenticity, etc.), value assessment, standout strengths/weaknesses, unique selling points."

Changed1 schema field changedJul 6, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "restaurant": {
+      "properties": {
+        "cuisine_tags": {
+          "items": {
+            "type": "string"
+          },
+          "type": "array"
+        },
+        "grade": {
+          "type": "string"
+        },
+        "grade_label": {
+          "type": "string"
+        },
+        "name": {
+          "type": "string"
+        },
+        "neighborhood": {
+          "type": "string"
+        },
+        "price_level": {
+          "type": "string"
+        },
+        "seemor_id": {
+          "type": "string"
+        },
+        "tldr": {
+          "type": "string"
+        }
+      },
+      "type": "object"
+    },
+    "status": {
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

First observedJul 6, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already cover readOnly/idempotent/non-destructive and openWorld=false, so the safety profile is free; the description goes well beyond by decoding coverage_level semantics ('full' carries a letter grade, 'basic' is a quick read with grade null and a preliminary_band, 'none' has no analysis). It also warns that premium dimension_assessments on quick-read rows are 'labelled on the same scale... but read from fewer reviews, so present them as preliminary' — a genuinely non-obvious caveat. It loses a point for not noting pagination, latency, or error behavior, but the data-semantics disclosure is substantial.

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

Conciseness3/5

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

The purpose and prerequisite are front-loaded, which is good, but the middle is a dense run-on that packs coverage_level, quick-read grading, field-level routing and the preliminary caveat into one serpentine sentence. Shorter sentences or a small structure would preserve the meaning with less parsing overhead, though the content itself earns its place.

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?

An output schema exists, so return values needn't be documented, yet the description still supplies the interpretation an agent needs (grade null vs. preliminary_band, preliminary vs. full analysis). Combined with annotations covering safety and a fully-described 2-param schema, nothing material for correct invocation is missing.

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 description coverage is 100%, so the baseline is 3 and the schema already documents both params including the full fields enum. The description still adds value by tying fields to data availability ('fully analyzed restaurants only, except the quick-read dimension_assessments below') and by explaining what the basic/default level actually returns, which the schema does not fully capture.

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 names a specific verb+resource ('Look up a specific restaurant by its Seemor ID') and enumerates the returned fields, then explicitly separates itself from siblings: single lookup vs. 'every result of recommend' and vs. search_restaurants/find_restaurant. An agent can pick it apart from all five siblings without opening a schema.

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?

It states the prerequisite ('Use search_restaurants or find_restaurant first to get restaurant IDs') and the exclusion ('not for every result of recommend'), so both the when and the when-not are explicit. The fields-level routing (basic/standard/premium) further tells the agent how to scope the call.

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

All Seemor Restaurant Intelligence tools Inspect

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

Need Help?