agentweb-mcp

batch_get_businesses

Retrieve up to 50 businesses in one API call using IDs or slugs, reducing round trips. Supports markdown, JSON, or shorthand output.

Instructions

Fetch up to 50 businesses in a single call by IDs or slugs. Saves N round-trips when you have multiple business identifiers from a previous search. Returns all businesses in one response. Supports prose (markdown), JSON, and shorthand formats.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ids": "<ids>"
    },
    "name": "batch_get_businesses"
  }
}

Input Schema

Name	Required	Description	Default
`ids`	Yes	Comma-separated business IDs or slugs (max 50). e.g. 'noma-copenhagen-abc12345,blue-bottle-sf-def67890'
`format`	No	Response format. 'text' (default) returns markdown prose. 'json' returns structured JSON. 'short' returns compact shorthand.	text

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.17.0Jun 21, 2026

TDQS

A3.9/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the batch behavior, format support, and limit of 50. However, it does not mention authentication requirements, rate limits, behavior on invalid IDs, or partial success/failure scenarios.

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 very concise, consisting of three short sentences that are front-loaded with the key purpose. Every sentence adds value, no fluff, and it efficiently conveys the tool's core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description partially explains return values (supports multiple formats). However, it lacks details on error handling, partial failures, or what happens if some IDs are invalid. For a batch tool, this is a notable gap, making it minimally complete.

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?

Both parameters have detailed descriptions in the schema (100% coverage). The description adds no additional semantic information beyond what the schema already provides for 'ids' (comma-separated) and 'format' (enum and default). Therefore, it meets the baseline but does not exceed schema coverage.

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 the tool fetches up to 50 businesses by IDs or slugs, using the verb 'fetch' and specifying the resource. It distinguishes itself from siblings like 'get_business' (single) and 'search_businesses' (search vs batch fetch) by emphasizing batching and saving round-trips.

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 provides clear context: use this tool when you have multiple business identifiers from a previous search to avoid multiple round-trips. However, it does not explicitly state when not to use it or compare with alternatives beyond the implied efficiency advantage.

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