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.
Q
QuerySculptor MCP Server
@flinstonedev
基本信息
关于 QuerySculptor MCP Server
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 配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"querysculptor": {
"command": "npx",
"args": [
"mcp-remote",
"https://agent-query-builder-toolbox.vercel.app/mcp",
"--allow-http"
]
}
}
}QuerySculptor MCP Server 工具
27Retrieve 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
概览
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
常见问题
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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