Skip to main content
Glama

validate

by io.github.machinegrade
OverviewDiscussionsAdmin

Server Details

Deterministic validation for AI-generated artifacts: JSON Schema, OpenAPI response, SQL syntax.

If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
Status
Healthy
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
Repository
machinegrade/validate
GitHub Stars
1
Server Listing
machinegrade-validate

TDQS

A3.7/5.0

Scored across 1 tool

Disambiguation5/5

There is only one tool, so there is no possibility of confusing it with others. The tool's purpose is clear and singular.

Naming Consistency5/5

With a single tool named 'validate', the naming is consistent and follows a simple verb format. There are no mixed conventions to cause confusion.

Tool Count2/5

The server has only one tool, which feels too few for any meaningful scope. Even for a narrow validation purpose, this is excessively minimal and likely to miss common requirements.

Completeness4/5

The tool covers the core validation action, supporting multiple contract types. However, it lacks ancillary operations such as batch validation, schema management, or result history, which are minor gaps for the stated purpose.

Available Tools

1 tool
validateAInspect

Validate an artifact against a contract (json_schema | openapi_response | sql) via the machinegrade validate API.

ParametersJSON Schema
NameRequiredDescriptionDefault
typeYesWhich validator to run.
artifactYesThe artifact to validate, as a JSON value — not a JSON-encoded string. json_schema/openapi_response: the object/array/value itself. sql: the SQL statement as a string.
contractNoValidator-specific contract. json_schema: { schema }. openapi_response: { spec, path, method, status }. sql: { dialect }.

TDQS

A3.6/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'validate' which implies a non-mutating check, but it does not describe return format, error behavior, or whether the operation is read-only. Key behavioral context is missing.

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 sentence that front-loads the core action and supported contract types. 'Via the machinegrade validate API' is slightly redundant but does not add significant noise. It is concise and to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has nested objects, no output schema, and no annotations, the description is insufficient. It does not explain what the validation response looks like, how to interpret results, or any error conditions, leaving the agent with significant ambiguity about expected outputs.

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% — all three parameters (type, artifact, contract) are described in detail. The description adds no additional parameter meaning beyond the enum values in the schema, so a baseline score of 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 the tool's purpose: 'Validate an artifact against a contract' and enumerates the supported contract types (json_schema | openapi_response | sql). This gives a specific verb, resource, and scope, making it obvious what the tool does.

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 implies when to use this tool by listing the three validator types, providing clear context for common validation scenarios. However, it does not explicitly mention alternatives or exclusions, as no sibling tools are present.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool update
    • Changedvalidate3 fields changed
      • changedInput schema / properties / artifact / description
        Previous value: -"The artifact to validate (object for json_schema/openapi_response, SQL string for sql)."New value: +"The artifact to validate, as a JSON value — not a JSON-encoded string. json_schema/openapi_response: the object/array/value itself. sql: the SQL statement as a string."
      • addedInput schema / properties / artifact / type
        Added value: +[
+  "object",
+  "array",
+  "string",
+  "number",
+  "boolean",
+  "null"
+]
      • addedInput schema / properties / contract / type
        Added value: +"object"
  2. 1 tool update
    • First observedvalidate

Related MCP Connectors

Related MCP Servers

Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources