QuerySculptor MCP Server

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flinstonedev

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flinstonedev

QuerySculptor MCP Server について

QuerySculptor is a GraphQL query builder designed for AI agents that provides 26 structured tools via the Model Context Protocol (MCP). Instead of generating complex GraphQL queries from scratch, AI agents can build queries step-by-step with real-time validation, schema introspec

#graphql #mcp #ai-agents#query-builder#typescript #model-context-protocol #claude #cursor #api-tools#schema-introspection#redis #vercel #serverless #developer-tools #llm-tools#chatbot-integration#automation #data-discovery#natural-language-queries#ai-powered#graph-queries#agent-tooling#pokemon-api#demo-api#query-validation#step-by-step-construction#error-prevention#incremental-building#session-management#rate-limiting #open-source#apache-license#nodejs #pnpm#vitest#testing#typescript-native#mcp-server#graphql-client#ai-assistant #conversational-ai#tool-framework#structured-queries#guided-construction#type-safety#real-time-validation#api-integration#developer-experience#query-optimization#rest-fallback#business-intelligence

QuerySculptor MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "querysculptor": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://agent-query-builder-toolbox.vercel.app/mcp",
        "--allow-http"
      ]
    }
  }
}

QuerySculptor MCP Server のツール

Retrieve the complete GraphQL schema definition for API understanding and exploration

Discover the available root operation types (Query, Mutation, Subscription) and their entry points

Get detailed information about a specific GraphQL type including fields, descriptions, and relationships

Get detailed information about a specific field within a GraphQL type including arguments and return type

Get guidance and field information for GraphQL input object types to help with argument construction

Initialize a new GraphQL query building session with persistent state management

Clean up and close a GraphQL query building session to free resources

Visualize the current GraphQL query structure and generated query string for debugging and review

Get suggestions for available fields that can be selected at a specific path in the query structure

Add a field to the GraphQL query structure with optional aliasing and validation

Add multiple fields to the GraphQL query structure in a single operation for efficiency

Define a GraphQL variable with its type and optional default value for use in the query

Assign a runtime value to a previously defined GraphQL variable for query execution

Remove a previously defined GraphQL variable from the query structure

Set string or enum arguments on GraphQL fields with automatic type detection and validation

Sets a typed argument (number, boolean, null) on a field in the GraphQL query structure.

Set nested properties within GraphQL input object arguments for complex data structures

Set a field argument to reference a GraphQL variable instead of a literal value

Create reusable named fragments for common field selections across queries

Apply a previously defined named fragment to a specific location in the query

Apply type-conditional field selections using inline fragments for union/interface types

Add GraphQL directives like @include or @skip to fields for conditional selection

Add directives to the root operation for query-level behavior control

Validate the built GraphQL query against the schema for syntax and semantic correctness

Execute the built GraphQL query against the configured endpoint and return results

Analyze the complexity, depth, and performance characteristics of the current query structure

Get current rate limit status for the client

概要

What is QuerySculptor?

QuerySculptor is a server application that helps AI agents interact with GraphQL APIs through structured tools instead of raw query generation. It provides 26 tools via the Model Context Protocol (MCP) for building, validating, and executing GraphQL queries step-by-step. It is designed for developers using AI agents like Cursor.

How to use QuerySculptor?

Add the public demo endpoint to your Cursor mcp.json configuration. For local setup, clone the repository, run pnpm install, copy example.env to .env and customize, then launch with vercel dev. The server becomes available at http://localhost:3000/mcp.

Key features of QuerySculptor

26 MCP tools for building GraphQL queries step-by-step
Step-by-step query building instead of raw string generation
Pre-configured public demo using the Pokemon API
Supports complex queries like union types and nested fields
Easily deployable locally via Vercel

Use cases of QuerySculptor

AI agents discovering Pokemon types, abilities, and moves
Exploring regional and species data with evolution chains
Building complex GraphQL queries for any API in small steps
Testing and validating GraphQL queries via structured tools

よくある質問

What does QuerySculptor do differently from raw GraphQL query generation?

QuerySculptor provides structured MCP tools that let agents build, validate, and execute queries step-by-step rather than generating complete query strings at once.

What are the runtime dependencies?

The server uses Node.js with pnpm and is deployed on Vercel. Clone the repo and install dependencies with `pnpm install`.

Where does the data live for the demo?

The demo is pre-configured to use the public Pokemon API (graphql-pokeapi.vercel.app). No local database is required.

Is there a public demo I can try?

Yes, the MCP endpoint is `https://agent-query-builder-toolbox.vercel.app/mcp` and works with the Pokemon API out of the box.

What transports does QuerySculptor use?

It uses HTTP via MCP, exposed as a URL endpoint (e.g., `/mcp`). No other transports or authentication are mentioned in the README.

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