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Glama

Openrouteservice

by io.github.pipeworx-io

Recall

recall
Read-onlyIdempotent

Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoMemory key to retrieve (omit to list all keys)

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: +[
+  {
+    "key": "user_research_topic"
+  },
+  {}
+]
  2. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds context: the tool retrieves saved values, can list keys, and is scoped to an identifier. It does not contradict annotations and provides additional behavioral details beyond them.

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 four sentences, each providing distinct value: purpose, usage examples, scope, and pairing. No redundant words, and the essential information is front-loaded.

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?

Despite no output schema, the description explains what is returned (value or list of keys) and covers scope and pairing. The tool is simple with one optional parameter, and the description is complete for an agent to use correctly.

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 description coverage is 100%, so baseline is 3. The description adds behavioral context by explaining that omitting the key lists all saved keys, which reinforces and clarifies the parameter's behavior beyond the terse schema description.

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 'Retrieve a value previously saved via remember, or list all saved keys' with a specific verb and resource. It distinguishes from siblings by mentioning remember (save) and forget (delete).

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

Usage Guidelines5/5

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

The description provides explicit usage context: 'look up context the agent stored earlier... without re-deriving it from scratch', examples of what to retrieve, and the scope ('Scoped to your identifier'). It implies when to use (when needing previously stored info) and alternatives via sibling references.

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

All Openrouteservice toolsInspect
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TDQS

B3.2/5.0
Disambiguation1/5

The tool set is a chaotic mix of geographic routing, AI visibility, betting analysis, memory storage, and random utilities. Many tools overlap in purpose (e.g., multiple data lookup tools like ask_pipeworx, discover_tools, resolve_entity), and the domain is completely inconsistent, making it nearly impossible for an agent to distinguish which tool to use for a given task.

Naming Consistency1/5

Tool names follow no consistent pattern; they mix snake_case (ai_visibility_check, ask_pipeworx), camelCase (generate_llms_txt), and arbitrary verbs without a clear verb_noun structure. Some names are vague (processV2-like patterns are absent, but e.g., 'forget' is a single verb). This chaotic naming prevents an agent from predicting tool functions.

Tool Count1/5

With 27 tools covering routing, AI marketing, betting, memory, and more, the count is extremely mismatched for the server's implied purpose ('Openrouteservice'). Even ignoring the name, the number is high and the scope is far too broad, making the set unwieldy and unfocused.

Completeness1/5

No coherent domain can be inferred from the tool set; it is an arbitrary collection. The routing tools are present but overshadowed by unrelated tools. For any single domain (e.g., betting or routing), the surface is either incomplete or includes extraneous tools, leaving the set severely lacking a clear purpose.

Resources