search_breweriesSearch for breweries by name. Returns location, phone, website, and contact details for matching results.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return (default 10, max 50) | |
| query | Yes | Brewery name or partial name to search for |
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | Number of breweries returned | |
| breweries | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "breweries": {
+ "items": {
+ "properties": {
+ "address": {
+ "description": "Full street address",
+ "type": "string"
+ },
+ "city": {
+ "description": "City name",
+ "type": "string"
+ },
+ "coordinates": {
+ "description": "Geographic coordinates if available",
+ "oneOf": [
+ {
+ "properties": {
+ "latitude": {
+ "description": "Latitude coordinate",
+ "type": "number"
+ },
+ "longitude": {
+ "description": "Longitude coordinate",
+ "type": "number"
+ }
+ },
+ "required": [
+ "latitude",
+ "longitude"
+ ],
+ "type": "object"
+ },
+ {
+ "type": "null"
+ }
+ ]
+ },
+ "country": {
+ "description": "Country name",
+ "type": "string"
+ },
+ "id": {
+ "description": "Brewery ID",
+ "type": "string"
+ },
+ "name": {
+ "description": "Brewery name",
+ "type": "string"
+ },
+ "phone": {
+ "description": "Phone number",
+ "type": "string"
+ },
+ "postal_code": {
+ "description": "Postal/zip code",
+ "type": "string"
+ },
+ "state": {
+ "description": "State or province",
+ "type": "string"
+ },
+ "type": {
+ "description": "Brewery type (e.g., micro, macro, pub)",
+ "type": "string"
+ },
+ "website": {
+ "description": "Website URL",
+ "type": "string"
+ }
+ },
+ "required": [
+ "id",
+ "name",
+ "type",
+ "address",
+ "city",
+ "state",
+ "postal_code",
+ "country",
+ "coordinates",
+ "phone",
+ "website"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "count": {
+ "description": "Number of breweries returned",
+ "type": "number"
+ }
+ },
+ "required": [
+ "count",
+ "breweries"
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {
+ "query": "Sierra Nevada"
+ },
+ {
+ "limit": 20,
+ "query": "Stone"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint, openWorldHint, idempotentHint, and destructiveHint annotations, the safety profile is already established. The description adds return details (location, phone, website, contact details) which is useful context beyond annotations. However, it doesn't disclose additional behaviors like rate limits or result ordering, so a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, front-loaded with the core purpose, and contains no filler. It earns a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool, the presence of an output schema, and comprehensive annotations, the description is sufficient for an agent to select and invoke the tool correctly. It includes what the tool does and what it returns, so a 5 is warranted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters have schema descriptions (100% coverage), so the schema already documents 'query' and 'limit'. The description's mention of 'by name' aligns with the query parameter but adds no new semantic information. Thus, baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search for breweries by name', providing a specific verb and resource. The phrase 'by name' differentiates this from sibling tools like 'breweries_by_city' and 'get_brewery', making its purpose distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear context for when to use the tool: when you need to search for breweries by name. However, it does not explicitly mention alternatives or exclusion criteria, such as 'use breweries_by_city for city-based searches', so it's a 4 rather than a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clear distinct purposes, but ask_pipeworx, ask_pipeworx_grounded, and deep_research overlap in querying Pipeworx data sources. Entity_profile and recent_changes also share some coverage. Overall, agents can differentiate, but a few pairs may cause confusion.
Tool names use snake_case for multi-word (e.g., ai_visibility_check) but also single-word verbs (forget, recall, remember). The pattern is not uniform: some are verb_noun, some are just noun or verb. Mixed conventions reduce predictability.
At 33 tools, the set is on the high side for an MCP server. The server covers a broad data-query domain, which justifies many specialized tools, but the count is borderline heavy and includes several meta-tools (discover_tools, suggest_questions). Could be streamlined without losing core functionality.
The tool surface is comprehensive for data retrieval across financial, economic, pharmaceutical, real estate, weather, and prediction markets. It includes both single-lookup and comparative tools, plus monitoring via subscriptions. Minor gaps exist (e.g., no direct update/delete for user memory beyond forget), but the core domain is well-covered.