Skip to main content
Glama

Tankerkoenig Stations Nearby

tankerkoenig_stations_nearby
Read-onlyIdempotent

German gas station fuel prices near a location — Benzinpreise Germany, real-time from the official MTS-K feed. Find the cheapest diesel, E5, or E10 near a point in Germany with price in EUR per liter, brand, address, distance, and open status. Coordinates are required: geocode a German city or address first (e.g. via a geocoding tool) — Berlin is lat 52.52, lng 13.40. Data covers Germany only. Example: tankerkoenig_stations_nearby({ latitude: 52.52, longitude: 13.40, radius_km: 5, fuel: "diesel", sort: "price" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fuelNoFuel type: "e5" (Super 95), "e10" (Super E10), "diesel", or "all" for all three prices per station (default "all")
sortNoSort order: "distance" (default) or "price" (cheapest first). Sorting by price requires a single fuel type (e5, e10, or diesel), the API rejects sort by price when fuel is "all"
_apiKeyNoOptional: your own free Tankerkoenig API key (creativecommons.tankerkoenig.de)
latitudeYesLatitude of the search center (Germany), e.g. 52.52 for Berlin
longitudeYesLongitude of the search center (Germany), e.g. 13.40 for Berlin
open_onlyNoReturn only stations that are currently open (default false)
radius_kmNoSearch radius in kilometers (default 5, maximum 25 — larger values are clamped)

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare the tool as read-only, open-world, idempotent, and non-destructive. The description adds that data is real-time from the MTS-K feed and mentions output fields like open status. It does not disclose potential rate limits, authentication requirements (beyond the optional _apiKey in schema), or any side effects. The description adds some but not extensive behavioral context beyond annotations.

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 efficient: four sentences that front-load the core purpose, then provide essential context (geocode first, Germany only), and end with a concrete example. Every sentence adds value; there is no fluff.

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?

Given the tool's moderate complexity (7 parameters, 2 required, enums, no output schema), the description adequately covers the purpose, prerequisite (geocode), geographic scope, and an example. It mentions output fields and open status. It does not describe the exact output structure (though no output schema exists), and it omits information about the _apiKey parameter in the description (though it's in the schema). Overall, it is sufficiently complete for a read-only tool.

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?

Schema coverage is 100%, so the baseline is 3. The description adds an example with concrete values and mentions that radius_km has a default of 5 and maximum of 25 (already in schema). It also implies sort constraints ('sort by price requires a single fuel type'), which is already detailed in the schema. The description does not substantially augment the schema's parameter documentation.

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's purpose: finding German gas station fuel prices near a location. It specifies the exact resources (diesel, E5, E10) and output fields (price, brand, address, distance, open status). The purpose is fully distinguished from sibling tools through its focus on nearby stations.

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 provides important usage context: it mentions that coordinates are required, advises geocoding first, and states data covers only Germany. However, it does not explicitly guide when to use this tool versus alternative tankerkoenig tools like tankerkoenig_prices or tankerkoenig_station_details, nor does it specify any exclusion criteria.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools occupy nearly identical roles: ask_pipeworx, ask_pipeworx_beta (explicitly identical right now), ask_pipeworx_grounded, and deep_research all answer research questions; polymarket_edges, bet_research, and polymarket_arbitrage overlap heavily on prediction-market opportunities; entity_profile, compare_entities, and recent_changes overlap on company research. The detailed descriptions help, but the clusters create real misselection risk.

Naming Consistency4/5

Nearly all tools follow a readable snake_case convention, many with verb_noun structure (resolve_entity, list_subscriptions, validate_claim, scan_dependency). Minor deviations exist: tankerkoenig_stations_nearby plural vs tankerkoenig_station_details/prices singular, plus noun-style names like pipeworx_feedback and pipeworx_trending, but the overall pattern is predictable.

Tool Count2/5

34 tools is heavy, and the problem is compounded by the server being named Tankerkoenig: only 3 of the 34 tools relate to German fuel prices while the other 31 are an unrelated Pipeworx/Polymarket/memory/subscription toolkit. This is a sprawling, unfocused surface rather than a well-scoped set.

Completeness3/5

For the nominal Tankerkoenig domain, stations_nearby + station_details + prices cover core lookups, though station search by name and price history are missing. For the broader bundled data/prediction-market domain, coverage is extensive but has notable gaps such as no trade execution, no general web search, and several redundant access paths that complicate the surface.