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Glama

Wolfram Alpha

by io.github.pipeworx-io

Full Query

full_query
Read-onlyIdempotent

Get the full structured result from Wolfram Alpha. Returns named "pods" (Input, Result, Solution, Plot, Properties, etc.) — useful when short_answer is too terse or you need multiple facets (e.g., element properties, equation solution + plot + alternate forms).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural-language query
unitsNometric | imperial (default metric)
formatNoplaintext (default) | plaintext,image — plaintext is most agent-friendly.
include_podsNoComma-separated pod IDs to restrict (e.g., "Result,Solution"). Default: return all.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
podsNoArray of result pods with structured data
tipsNoUsage tips from Wolfram Alpha
queryYesThe query string that was sent to Wolfram Alpha
messageNoError message if success is false
successYesWhether Wolfram Alpha found a valid interpretation
pod_countNoNumber of result pods returned
did_you_meanNoSuggested alternative interpretations

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "query": "solve x^2 - 5x + 6 = 0"
+  },
+  {
+    "include_pods": "Result,Properties",
+    "query": "properties of gold"
+  },
+  {
+    "format": "plaintext",
+    "query": "current time in Tokyo"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "did_you_mean": {
+      "description": "Suggested alternative interpretations",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "message": {
+      "description": "Error message if success is false",
+      "type": "string"
+    },
+    "pod_count": {
+      "description": "Number of result pods returned",
+      "type": "integer"
+    },
+    "pods": {
+      "description": "Array of result pods with structured data",
+      "items": {
+        "properties": {
+          "contents": {
+            "description": "Plain-text content from all subpods joined by newlines",
+            "type": "string"
+          },
+          "id": {
+            "description": "Pod identifier",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "images": {
+            "description": "URLs of images in this pod",
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "position": {
+            "description": "Display position of the pod",
+            "type": [
+              "integer",
+              "null"
+            ]
+          },
+          "primary": {
+            "description": "Whether this is the primary result pod",
+            "type": "boolean"
+          },
+          "title": {
+            "description": "Pod title (e.g., 'Input', 'Result', 'Solution')",
+            "type": [
+              "string",
+              "null"
+            ]
+          }
+        },
+        "required": [
+          "title",
+          "id",
+          "primary",
+          "position",
+          "contents",
+          "images"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "query": {
+      "description": "The query string that was sent to Wolfram Alpha",
+      "type": "string"
+    },
+    "success": {
+      "description": "Whether Wolfram Alpha found a valid interpretation",
+      "type": "boolean"
+    },
+    "tips": {
+      "description": "Usage tips from Wolfram Alpha",
+      "type": [
+        "string",
+        "null"
+      ]
+    }
+  },
+  "required": [
+    "query",
+    "success"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable context about return structure (named pods) and gives examples of pod types, complementing the annotations without contradicting 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?

Two sentences, front-loaded with the main purpose, then concise examples of use cases. No waste or redundancy.

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?

With an output schema available and annotations covering safety, the description provides the key contextual information: what the tool returns, when to use it, and examples of use cases. This is complete for a read-only query 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 description coverage is 100%, so all four parameters are already described. The description mentions 'pods' and 'include_pods' implicitly through examples, but adds no new parameter semantics beyond what the schema provides. Baseline 3 is appropriate.

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 what the tool does: 'Get the full structured result from Wolfram Alpha' with a specific verb and resource. It also distinguishes it from the sibling short_answer by explaining it returns named pods and is useful when more detail is needed.

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 explicitly says 'useful when short_answer is too terse or you need multiple facets', providing a clear when-to-use condition and implicitly excluding the alternative. This helps an agent choose between full_query and short_answer.

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

A3.7/5.0
Disambiguation2/5

Several tools are near-indistinguishable: ask_pipeworx and ask_pipeworx_beta are currently identical, and ask_pipeworx/ask_pipeworx_grounded/deep_research have overlapping routing behavior. discover_tools vs suggest_questions and ai_visibility_check vs scan_competitor_ai_presence also create boundary ambiguity, making misselection likely for agents.

Naming Consistency2/5

Names mix bare verbs (recall, remember, forget), brand-prefixed nouns (pipeworx_trending, polymarket_edges), and descriptive phrases (generate_llms_txt, scan_competitor_ai_presence). There is no consistent verb_noun or prefix convention, and the server name 'Wolfram Alpha' does not match the dominant pipeworx_/polymarket_ naming.

Tool Count2/5

At 34 tools, the set exceeds the 25+ threshold and feels heavy even for a broad data platform. Several unrelated add-ons (memory trio, ai_visibility, generate_llms_txt, scan_dependency) could live in separate servers, contributing to bloat and diluting the core purpose.

Completeness3/5

The data-research and prediction-market surfaces are fairly thorough (routing, grounded verification, deep research, entity resolution, comparisons, subscriptions), but the Wolfram Alpha core is thin—only short_answer, full_query, and wolfram_compute—with no step-by-step solutions, units catalog, or history. The mismatched server name and unrelated tools indicate an incoherent scope with notable gaps.

Resources