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Glama

Schemastore

by io.github.pipeworx-io

Find Schema For

find_schema_for
Read-onlyIdempotent

Match a config filename against the SchemaStore catalog (schemastore.org) to find which JSON Schemas declare a fileMatch glob covering it, for example package.json, tsconfig.json, or .github/workflows/ci.yml. Returns the matching catalog entries with schema name, description, fileMatch globs, and the json.schemastore.org schema URL. Answers which JSON Schema validates a given config file so an editor or linter can be pointed at it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filenameYese.g. package.json, .github/workflows/ci.yml

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
matchesYesCatalog entries with matching fileMatch globs
filenameYesInput filename searched

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: +[
+  {
+    "filename": "package.json"
+  },
+  {
+    "filename": ".github/workflows/ci.yml"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "filename": {
+      "description": "Input filename searched",
+      "type": "string"
+    },
+    "matches": {
+      "description": "Catalog entries with matching fileMatch globs",
+      "items": {
+        "properties": {
+          "description": {
+            "description": "Schema description",
+            "type": "string"
+          },
+          "fileMatch": {
+            "description": "Glob patterns matching filenames",
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "name": {
+            "description": "Schema name",
+            "type": "string"
+          },
+          "url": {
+            "description": "Schema URL",
+            "type": "string"
+          },
+          "versions": {
+            "additionalProperties": {
+              "type": "string"
+            },
+            "description": "Schema versions mapping",
+            "type": "object"
+          }
+        },
+        "required": [
+          "name",
+          "url"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "filename",
+    "matches"
+  ],
+  "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 read-only, idempotent, and non-destructive behavior. The description adds the matching logic and what is returned (schema name, description, fileMatch globs, URL), which is useful context beyond the 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 three sentences, each earning its place: purpose, examples, return payload, and use case. No fluff or repetition.

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 the simple one-parameter tool, presence of an output schema, and comprehensive annotations, the description fully covers the tool's function, return values, and use case. No missing critical information.

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 schema fully describes the filename parameter (100% coverage), so the baseline is 3. The description reinforces with examples like package.json and .github/workflows/ci.yml, adding clarity about what constitutes a config filename.

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 states a specific action: 'Match a config filename against the SchemaStore catalog...' and explains it returns matching catalog entries. It clearly distinguishes from sibling tools like fetch_schema by focusing on identifying which JSON Schema validates a given config file.

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 gives clear context: use when you need to determine which JSON Schema validates a config file, with the explicit purpose of pointing an editor or linter. It does not explicitly name alternatives or state when not to use it, but the use case is well-defined.

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

A3.8/5.0
Disambiguation3/5

Several tools occupy overlapping semantic space: ask_pipeworx, ask_pipeworx_beta (currently identical), and ask_pipeworx_grounded are the same router in different modes, while suggest_questions and discover_tools both serve capability discovery. The detailed descriptions help, but an agent could easily select the wrong entry point, especially among the prediction-market and router variants.

Naming Consistency4/5

All tool names use lowercase snake_case and mostly follow a verb_noun pattern (fetch_schema, resolve_entity, validate_claim), with some domain-prefixed nouns (polymarket_edges, pipeworx_trending) and a few adjective_noun outliers (recent_alerts, recent_changes). The convention is consistent and predictable, with only minor deviations.

Tool Count2/5

At 35 tools, the set is far too large for a server named Schemastore — only four tools relate to the schema catalog while the rest form a sprawling data-research, prediction-market, memory, and subscription platform. The count is heavy and the scope feels unfocused.

Completeness3/5

The broad data-research and prediction-market domain is well covered — lookup, compare, validate, research, arbitrage, subscriptions, and memory all have lifecycle support — but the server's namesake purpose (schema catalog) is thinly served by four read-only tools with no way to contribute or manage schemas. The domain mismatch makes the surface feel both over- and under-complete.

Resources