Lokuli: book local pros and get prices

Find local businesses on Lokuli

find_businesses

Read-onlyIdempotent

Searches Lokuli for local service businesses near a US zip code or city. Most businesses on Lokuli are in California, a few in other states. Understands everyday and Spanish wording ("deep clean", "fade", "mani pedi", "limpieza de casa"). Returns businesses that can be booked through Lokuli, with their services, prices and service ids, each marked with how it matched (name, service, synonym, or trade, meaning the same kind of business), and, separately, businesses from public records that are not on Lokuli and can't be booked.

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": {
      "service": "<service>"
    },
    "name": "find_businesses"
  }
}

Input Schema

Name	Required	Description
`zip`	No	5-digit zip code to search near
`city`	No	City, if there's no zip (e.g. "Montebello")
`limit`	No	Most results per group (default 6)
`service`	Yes	What the person needs, in plain words: "haircut", "dog grooming", "brake repair"

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 1, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), and the description adds context the annotations cannot carry: the dataset is concentrated in California, colloquial English/Spanish phrasing is understood, and results are split into bookable Lokuli businesses versus public-record businesses that cannot be booked. That two-tier return structure is exactly the behavioral detail an agent needs before choosing follow-up calls.

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?

Purpose is front-loaded in the first sentence, then coverage bias, language handling, and return shape follow in a logical order. It is dense but every sentence carries information; the parenthetical examples are the only mildly padded element.

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?

With no output schema, the description carries the burden of explaining returns and does so well (services, prices, service ids, match markers, non-bookable group). It stops short of covering edge cases such as no results or an unsupported zip, so it is strong but not exhaustive.

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 coverage is 100%, so baseline is 3. The description goes beyond the schema by explaining that 'service' accepts everyday and Spanish wording and is matched by name, service, synonym, or trade, which materially changes how an agent should phrase that parameter. It omits any guidance on 'limit' or on zip/city precedence beyond what the schema already says.

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?

States a specific verb and resource ('Searches Lokuli for local service businesses') plus the locational scope (US zip code or city). It is clearly distinct from siblings like get_business (detail lookup) and check_coverage (coverage query) without the reader needing to open another schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the use case (find businesses by service near a location) and signals which returned results are bookable, hinting at the follow-on to book_appointment. However, it never names an alternative sibling or states when not to use this tool, so the routing guidance is inferential rather than explicit.

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

All Lokuli: book local pros and get prices 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?