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mcp-graphql

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mcp-graphql

Schmiedeabzeichen

Ein Model Context Protocol-Server, der LLMs die Interaktion mit GraphQL-APIs ermöglicht. Diese Implementierung bietet Funktionen zur Schema-Introspektion und Abfrageausführung, sodass Modelle GraphQL-APIs dynamisch erkennen und nutzen können.

Verwendung

Führen Sie mcp-graphql mit dem richtigen Endpunkt aus. Es wird automatisch versucht, Ihre Abfragen zu überprüfen.

Umgebungsvariablen (wichtige Änderung in 1.0.0)

Hinweis: Ab Version 1.0.0 wurden Befehlszeilenargumente durch Umgebungsvariablen ersetzt.

Umgebungsvariable

Beschreibung

Standard

ENDPOINT

GraphQL-Endpunkt-URL

http://localhost:4000/graphql

HEADERS

JSON-String mit Headern für Anfragen

{}

ALLOW_MUTATIONS

Mutationsvorgänge aktivieren (standardmäßig deaktiviert)

false

NAME

Name des MCP-Servers

mcp-graphql

SCHEMA

Pfad zu einer lokalen GraphQL-Schemadatei (optional)

-

Beispiele

# Basic usage with a local GraphQL server
ENDPOINT=http://localhost:3000/graphql npx mcp-graphql

# Using with custom headers
ENDPOINT=https://api.example.com/graphql HEADERS='{"Authorization":"Bearer token123"}' npx mcp-graphql

# Enable mutation operations
ENDPOINT=http://localhost:3000/graphql ALLOW_MUTATIONS=true npx mcp-graphql

# Using a local schema file instead of introspection
ENDPOINT=http://localhost:3000/graphql SCHEMA=./schema.graphql npx mcp-graphql

Related MCP server: mcp4gql

Ressourcen

  • graphql-schema : Der Server stellt das GraphQL-Schema als Ressource bereit, auf die Clients zugreifen können. Dies ist entweder die lokale Schemadatei oder basiert auf einer Introspektionsabfrage.

Verfügbare Tools

Der Server bietet zwei Haupttools:

  1. introspect-schema : Dieses Tool ruft das GraphQL-Schema ab. Verwenden Sie es zuerst, wenn Sie keinen Zugriff auf das Schema als Ressource haben. Es verwendet entweder die lokale Schemadatei oder eine Introspektionsabfrage.

  2. query-graphql : Führt GraphQL-Abfragen für den Endpunkt aus. Standardmäßig sind Mutationen deaktiviert, es sei denn, ALLOW_MUTATIONS ist auf true gesetzt.

Installation

Installation über Smithery

So installieren Sie GraphQL MCP Server für Claude Desktop automatisch über Smithery :

npx -y @smithery/cli install mcp-graphql --client claude

Manuelle Installation

Es kann manuell auf Claude installiert werden:

{
    "mcpServers": {
        "mcp-graphql": {
            "command": "npx",
            "args": ["mcp-graphql"],
            "env": {
                "ENDPOINT": "http://localhost:3000/graphql"
            }
        }
    }
}

Sicherheitsüberlegungen

Mutationen sind standardmäßig aus Sicherheitsgründen deaktiviert, um zu verhindern, dass ein LLM Ihre Datenbank- oder Servicedaten ändert. Überlegen Sie gut, bevor Sie Mutationen in Produktionsumgebungen aktivieren.

Anpassen für Ihren eigenen Server

Dies ist eine sehr generische Implementierung, die vollständige Selbstbeobachtung ermöglicht und Ihren Benutzern freie Hand lässt (einschließlich Mutationen). Wenn Sie eine spezifischere Implementierung benötigen, empfehle ich Ihnen, einfach ein eigenes MCP zu erstellen und ein Tool zu sperren, das Clients nur die Eingabe bestimmter Abfragefelder und/oder Variablen erlaubt. Sie können dies als Referenz verwenden.

Available Tools

2 tools
introspect-schemaA

Introspect the GraphQL schema, use this tool before doing a query to get the schema information if you do not have it available as a resource already.

ParametersJSON Schema
NameRequiredDescriptionDefault
endpointNoOptional: Override the default endpoint, the already used endpoint is: http://localhost:3000/graphql
headersNoOptional: Add additional headers, the already used headers are: {}

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. The description mentions timing ('before doing a query') but doesn't explain what the introspection actually returns, whether it's a one-time operation or cached, what format the schema information comes in, or any authentication/rate limit considerations. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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, efficient sentence that front-loads the core purpose ('Introspect the GraphQL schema') followed by usage guidance. Every word earns its place with no redundancy or unnecessary elaboration. The structure is clear and appropriately sized for the tool's complexity.

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

Completeness3/5

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

Given the tool has no output schema and no annotations, the description should do more to explain what the introspection returns and any behavioral considerations. While it adequately covers purpose and basic usage, it lacks details about the return format, error conditions, or operational characteristics that would help an agent use it effectively. The description is minimally viable but has clear gaps in completeness.

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 the schema already documents both parameters thoroughly with descriptions of their optional nature and default values. The description adds no parameter-specific information beyond what's in the schema. With high schema coverage, the baseline score of 3 is appropriate since the description doesn't need to compensate for schema gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('introspect') and resource ('GraphQL schema'), and specifies the purpose is to 'get the schema information'. It distinguishes from the sibling tool 'query-graphql' by indicating this is for schema discovery rather than query execution. However, it doesn't explicitly contrast with the sibling beyond implied timing ('before doing a query').

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 provides clear context on when to use this tool: 'before doing a query to get the schema information if you do not have it available as a resource already'. It implies an alternative (having the schema as a pre-existing resource) and gives timing guidance. However, it doesn't explicitly state when NOT to use it or provide detailed comparison with the sibling tool beyond the basic distinction.

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

query-graphqlC

Query a GraphQL endpoint with the given query and variables

ParametersJSON Schema
NameRequiredDescriptionDefault
endpointNoOptional: Override the default endpoint, the already used endpoint is: http://localhost:3000/graphql
headersNoOptional: Add additional headers, the already used headers are: {}
queryYes
variablesNo

TDQS

C2.9/5.0
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 mentions the action but lacks details on permissions, rate limits, error handling, or response format. This is inadequate for a tool that interacts with an external endpoint, leaving significant gaps in understanding its behavior.

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, efficient sentence with zero waste. It is appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.

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 complexity of querying a GraphQL endpoint, no annotations, no output schema, and incomplete parameter documentation, the description is insufficient. It fails to address critical aspects like authentication, response structure, or error scenarios, making it incomplete for effective tool use.

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 50% (2 out of 4 parameters have descriptions). The description adds minimal value beyond the schema, as it only mentions 'query and variables' without explaining their formats or relationships. It doesn't compensate for the undocumented parameters (query and variables lack schema descriptions), resulting in a baseline score due to partial coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Query') and resource ('a GraphQL endpoint'), specifying what the tool does. It distinguishes from the sibling 'introspect-schema' by focusing on general query execution rather than schema introspection, though it doesn't explicitly mention this distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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. The description doesn't mention the sibling tool 'introspect-schema' or any other context for selection. It simply states the action without usage context.

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. 2 tool updatesv1.0.0
    • First observedintrospect-schema
    • First observedquery-graphql
Deploy Server
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TDQS

B3.1/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: introspect-schema retrieves schema information, while query-graphql executes queries. There is no overlap or ambiguity between them, making it easy for an agent to select the correct tool.

Naming Consistency3/5

The tools use a verb-noun pattern (introspect-schema, query-graphql), which is consistent. However, the hyphenated naming style is less common than snake_case or camelCase, and with only two tools, it's hard to assess full consistency, but they follow the same convention.

Tool Count2/5

With only two tools, the server feels thin for a GraphQL domain, which typically involves operations like mutations, subscriptions, or schema updates. While core querying is covered, the scope is limited, potentially requiring agents to work around missing functionality.

Completeness2/5

The server covers basic introspection and querying but lacks essential GraphQL operations like mutations (for data modification) or subscriptions (for real-time updates). This creates significant gaps that could lead to agent failures when full lifecycle management is needed.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

Resources

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