Skip to main content
Glama

Graphql Audit

graphql_audit
Read-only

Audit GraphQL endpoints by testing introspection, suggestions, GraphiQL, CSRF, and trace mode vulnerabilities.

Instructions

Audit a GraphQL endpoint: introspection, suggestions, GraphiQL, CSRF, trace mode.

Passive. Every check that remains is a single well-formed query used to read what the server discloses. graphql-cop's denial-of-service family (alias overloading, batching, directive overloading, circular introspection) is excluded unconditionally — those exist to make the server burn CPU, which is out of bounds under scope.rules.no_dos.

If the URL has no path, graphql-cop tries /, /graphql, /graphiql, /playground and /console; give it the exact path to keep the request count down.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv2.1.0

TDQS

A4.7/5.0
Behavior5/5

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

The description states the tool is passive and every check is a single well-formed read query, aligning with the readOnlyHint and destructiveHint annotations. It further discloses that DoS-related checks are unconditionally excluded, providing transparent behavior beyond the annotation metadata.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is organized into three focused paragraphs: purpose, safety/scope, and URL/path guidance. It is slightly verbose with the repeated graphql-cop references, but each sentence adds meaningful information and no filler is present.

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

Completeness4/5

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

The description provides enough context about what the audit covers, its passive nature, and its path-finding behavior. Since an output schema exists, not detailing return values is acceptable. It lacks only a brief note on how results are delivered, but this does not impair usability.

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 only says target is a required string, but the description gives useful semantic context: target is a URL and path behavior is explained, including what happens when no path is provided. It does not explicitly label target as 'the GraphQL endpoint URL', but the connection is strongly implied.

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 audits a GraphQL endpoint and enumerates concrete checks: introspection, suggestions, GraphiQL, CSRF, and trace mode. This distinctively separates it from sibling tools like code_audit or cloud_audit, and the verb-resource relationship is explicit.

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 gives explicit usage guidance: it is passive, uses only read-style queries, and excludes the denial-of-service family under scope.rules.no_dos. It also advises providing an exact path when the URL has none, which directly helps the agent use the tool efficiently and safely.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/iamsecure1920/Cordon-AI'

If you have feedback or need assistance with the MCP directory API, please join our Discord server