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Glama

Here

by io.github.pipeworx-io

Here Route

here_route
Read-onlyIdempotent

TRAFFIC-AWARE routing and ETA between two locations via HERE — "how long to drive from Berlin to Munich", "ETA from LAX to downtown LA in traffic", "cycling route from A to B". Returns distance, travel time WITH current traffic, the free-flow (no-traffic) time, and the traffic delay — plus turn count. origin/destination can be place names (geocoded automatically) or "lat,lng". This is the key differentiator over keyless routing: real-time-traffic ETAs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
originYesStart — place name (e.g. "LAX airport") or "lat,lng".
destinationYesEnd — place name (e.g. "downtown Los Angeles") or "lat,lng".
transport_modeNocar (default) | truck | pedestrian | bicycle | scooter.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "destination": "downtown Los Angeles",
+    "origin": "LAX airport",
+    "transport_mode": "car"
+  },
+  {
+    "destination": "Munich",
+    "origin": "Berlin",
+    "transport_mode": "truck"
+  }
+]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate readOnly, idempotent, and no side effects. The description adds behavioral details: returns distance, travel times (with traffic, free-flow, delay), and turn count. No contradictions with 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 a single, well-structured paragraph. It front-loads the key differentiator ('TRAFFIC-AWARE'), includes examples, and is concise with no wasted words.

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 high-quality annotations and schema, the description is complete. It explains return values (distance, times, turn count) and input flexibility. While no output schema exists, the description compensates adequately.

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?

Input schema has 100% coverage, so baseline is 3. The description enhances this with examples and clarifies that origin/destination can be place names or lat,lng, and transport_mode defaults. This adds value beyond the schema.

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 uses specific verbs ('routing and ETA') and clearly identifies the resource (HERE) and key differentiator (traffic-aware, real-time traffic ETAs). It distinguishes itself from sibling tools like here_geocode and here_reverse_geocode by focusing on routing with traffic.

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 on when to use (traffic-aware routing), includes examples, and mentions constraints (origin/destination can be place names or lat,lng). However, it does not explicitly state when not to use or name alternatives among siblings, though the differentiation from 'keyless routing' is implicit.

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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TDQS

A3.9/5.0
Disambiguation2/5

Several tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and suggest_questions all route questions to the same underlying data catalog, making it hard to pick the right one. The Polymarket-related tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_edge_tracker, polymarket_kalshi_spread) also have overlapping discovery and analysis purposes.

Naming Consistency3/5

Many tools use descriptive snake_case, and the ask_pipeworx family shares a clear prefix, but the set mixes generic memory verbs (remember, recall, forget), brand-prefixed tools (here_*, pipeworx_*), and standalone names like bet_research and scan_dependency. There is no consistent verb_noun pattern across the whole server.

Tool Count2/5

35 tools is heavy for a single MCP server, and a large portion are meta-tools layered over the same 5,752-tool catalog (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, suggest_questions). The broad intentional scope explains the count, but the tool surface feels bloated and harder to navigate than it needs to be.

Completeness4/5

The domain is unusually broad—data querying, entity resolution, comparison, monitoring, memory, geolocation, prediction markets, dependency scanning—and the set covers most workflows end to end. Minor gaps exist, like no direct pipeworx:// citation fetcher and no update/list/delete pattern for entity profiles, but the core user journeys are well supported.

Resources