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flowteller-io

Flowteller API MCP Server

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search_trips

Search for trips between an origin and destination on a specific date. Provide travel date, passenger counts, and provider to retrieve available booking options.

Instructions

Search for available trips between an origin and destination on a specific date.

Args:
    origin_name: The name of the origin location (e.g., 'Mwanza').
    destination_name: The name of the destination location (e.g., 'Dodoma').
    travel_date: The travel date in YYYY-MM-DD format.
    provider: The booking provider name. Default is 'bus'.
    adults: Number of adult passengers.
    children: Number of child passengers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
adultsNo
childrenNo
providerNobus
origin_nameYes
travel_dateYes
destination_nameYes
Behavior3/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It communicates that this is a search operation (read-only by implication) and provides parameter details, but it does not disclose potential behaviors like result limits, pagination, error handling, or date validation nuances. This adds some value but lacks rich context.

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 concise and well-structured: an opening sentence states the purpose, followed by a bulleted Args list. Every line provides useful information, with no redundant or vague content, and the parameter details are easy to scan.

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?

The description covers all parameters thoroughly and mentions defaults, but it does not describe the output format or behavior when no trips are found. There is also no mention of prerequisites like valid location names from get_origins/get_destinations. Given the lack of annotations and output schema, these gaps make the description adequate but not fully complete.

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?

The schema has 0% description coverage, so the description must compensate. It provides clear meaning for each parameter: examples for origin_name and destination_name, a format for travel_date, and defaults for provider, adults, and children. It could add constraints like minimum values for adults, but overall it effectively explains all parameters.

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 'Search for available trips between an origin and destination on a specific date,' using a specific verb and resource. It distinguishes itself from siblings like get_origins/get_destinations by focusing on trip search, and from create_booking by being a search rather than a booking action.

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 when to use the tool (when searching for trips) but does not explicitly state exclusions or mention alternative tools. There is no guidance on when not to use it or how it relates to other sibling tools like get_origins or create_booking, leaving the agent to infer the intended use case.

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

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