list_schemasList SchemaStore catalog entries. Optional case-insensitive filter on name/description/fileMatch.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 1-500 (default 50) | |
| filter | No | e.g. "github", "tsconfig", "openapi" |
| Name | Required | Description | Default |
|---|---|---|---|
| total | Yes | Total number of schemas in catalog | |
| matches | Yes | Number of schemas matching the filter | |
| results | Yes | Filtered catalog entries (up to limit) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "filter": "github",
+ "limit": 10
+ },
+ {
+ "filter": "openapi"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "matches": {
+ "description": "Number of schemas matching the filter",
+ "type": "number"
+ },
+ "results": {
+ "description": "Filtered catalog entries (up to limit)",
+ "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"
+ },
+ "total": {
+ "description": "Total number of schemas in catalog",
+ "type": "number"
+ }
+ },
+ "required": [
+ "total",
+ "matches",
+ "results"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate the tool is read-only, non-destructive, idempotent, and open-ended. The description adds that filtering is case-insensitive and applies to name, description, and fileMatch. This provides additional behavioral 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 16 words, efficiently conveying the essential behavior. It is front-loaded with the main action and includes the key detail about filtering. No unnecessary verbiage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and comprehensive annotations, the description adequately covers the tool's functionality. It explains the filtering capability but does not mention pagination or limit behavior beyond what is in the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema describes both parameters with basic examples. The description clarifies that the filter is case-insensitive and applies to specific fields (name, description, fileMatch), which adds meaning beyond the schema's simple examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists SchemaStore catalog entries and mentions the optional filter. The purpose is specific, but it does not explicitly differentiate from sibling tools like 'fetch_schema' or 'find_schema_for', which are also schema-related.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, if a user needs a specific schema, they might prefer 'fetch_schema' or 'find_schema_for' instead. The description only mentions the filter capability without explaining when it is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.