MapMap

order_stops

Put a single run's stops in the best visiting order ("order my errands"). Provide start {lat, lon} and stops (1-100 entries of {location, label?, service_s?}); optionally an end destination or round_trip: true to return to the start. Costing "auto" = car, "truck" = lorry (pass truck as in route for a truck-legal order). Returns the stops in visit order with arrival offsets in seconds, plus total duration and distance.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`end`	No	Optional fixed final destination. Mutually exclusive with `round_trip`; omitted (and not a round trip), the run ends at whichever stop the solver visits last.
`start`	Yes	Where the run starts.
`stops`	Yes	The stops to put in the best visiting order (1–100).
`truck`	No	Truck profile (dimensions + ADR declaration); requires costing "truck". The travel-time matrix then respects dimensional and dangerous-goods restrictions.
`costing`	No	Costing model: "auto" (default) or "truck".	auto
`round_trip`	No	Return to `start` after the last stop (default false).

Output Schema

TableJSON Schema

Name	Required	Description
`ordered`	Yes	The stops in optimal visiting order.
`profile`	Yes	The matrix costing profile ("auto" or "truck").
`distance_m`	No	Total travel distance in metres, when reported.
`duration_s`	Yes	Total travel time in seconds.
`unassigned_stop_indexes`	Yes	0-based indexes of stops the solver could not fit (empty in the normal, unconstrained case).

TDQS

A4.3/5.0

Behavior4/5

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

No annotations are provided, so the description carries the full behavioral burden. It clearly discloses the output contract: stops in visit order, arrival offsets in seconds, plus total duration and distance, and it clarifies truck mode produces a truck-legal order. It does not mention statelessness or failure behavior, but as a pure computation tool the disclosure is adequate.

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?

Three dense sentences front-load the purpose before parameter details, with no filler. Each sentence adds distinct information while keeping the whole description readable and scannable.

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?

Given that an output schema exists and the input schema fully documents each parameter, the description is complete enough for correct invocation. It covers required inputs, the 1–100 stop limit, optional end/round_trip behavior, costing selection, truck-legal ordering, and the return value shape without needing to repeat schema details.

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 input schema already documents all parameters (100% coverage), so the baseline is 3. The description adds human-readable meaning: auto=car, truck=lorry, a compact stop shape of {location, label?, service_s?}, and a pointer to route's truck syntax, all of which help an agent map intent to 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?

States a specific operation: "Put a single run's stops in the best visiting order," reinforced by the quoted user intent "order my errands". The phrase "single run's stops" separates it from broader fleet tools like optimise_routes and from route geometry tools, so an agent can identify what it does precisely.

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 gives practical configuration guidance: optional end vs round_trip, costing auto vs truck, and passing truck as in route. However, it never explicitly says when to choose this tool over optimise_routes, route, or matrix; the use case is implied rather than stated with when-not-to-use conditions.

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

All MapMap tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0

Disambiguation4/5

Most tools target a distinct action and resource pair, and descriptions are explicit about which tool fits which scenario. The closest overlaps—plan_ev_route vs cheapest_charging_along_route, and route vs plan_day vs order_stops vs optimise_routes—are mitigated by clear guidance, so an agent can usually pick correctly.

Naming Consistency4/5

Tool names overwhelmingly follow a verb_noun snake_case pattern (plan_ev_route, set_palette, list_style_layers) with a consistent geo_ prefix for geometry helpers. Minor deviations like elevation, route, and matrix are short and readable but break the strict verb_noun convention.

Tool Count2/5

At 39 tools, this surface is well past the 25+ threshold and feels heavy even for a broad mapping platform. The set spans routing, geocoding, places, styles, EV/fuel, telematics, usage, and feedback, which would be easier for an agent to navigate if split into smaller domain-focused servers.

Completeness4/5

For the stated breadth, coverage is strong: routing, multi-stop planning, VRP, EV/fuel detours, geocoding, places, geometry, style lifecycle, and telematics all have workable primary paths. Minor gaps like no style deletion, no route alternatives, and no batch geocoding are present but do not create dead ends for core workflows.

Resources

Need Help?