mcp-graphql
MCP ServerFreeModel Context Protocol server for GraphQL
Capabilities8 decomposed
graphql schema introspection via mcp resource
Medium confidenceExposes GraphQL schema as a named MCP resource (graphql-schema) that LLMs can access through the Model Context Protocol. The server implements schema discovery by either introspecting a live GraphQL endpoint using the GraphQL introspection query or reading a pre-cached local schema file, then serializes the complete type system (types, fields, arguments, directives) as a structured resource that LLM clients can reference in their context without re-fetching.
Implements schema exposure as a first-class MCP resource rather than a tool output, allowing LLM clients to reference the schema in their context window persistently and efficiently without repeated tool calls. Supports both live endpoint introspection and local schema file fallback for offline/cached scenarios.
Unlike REST API documentation tools that require LLMs to parse markdown specs, mcp-graphql provides structured, queryable schema metadata that LLMs can reason about directly, and unlike generic GraphQL clients, it's optimized for LLM context management via MCP's resource protocol.
graphql query execution with variable binding
Medium confidenceImplements a query-graphql tool that accepts a GraphQL query string and optional variables object, then executes the query against a configured GraphQL endpoint using HTTP POST with proper header injection and response parsing. The tool validates query syntax before execution, binds variables to the query using GraphQL's variable substitution mechanism, and returns the full response (data + errors) to the LLM, enabling dynamic query construction and parameterized operations.
Implements query execution as an MCP tool with built-in variable binding support, allowing LLMs to construct parameterized queries without string interpolation. Includes mutation-safety by default (disabled unless explicitly enabled) and passes through full GraphQL response semantics (data + errors) rather than flattening results.
More secure than generic HTTP tools because it enforces GraphQL syntax and can disable mutations by default; more flexible than pre-built query libraries because it allows LLMs to construct arbitrary queries dynamically; cleaner than REST API wrappers because GraphQL's type system provides better context for LLM reasoning.
mcp server lifecycle management with stdio transport
Medium confidenceImplements a full Model Context Protocol server using the @modelcontextprotocol/sdk that manages the complete MCP lifecycle: server initialization with name/version metadata, resource and tool registration, stdio-based bidirectional communication with MCP clients, and graceful shutdown. The server uses Node.js stdio streams (stdin/stdout) as the transport layer, enabling seamless integration with MCP-compatible clients like Claude Desktop and Cline without requiring HTTP/WebSocket infrastructure.
Uses Node.js stdio streams as the MCP transport layer, eliminating the need for HTTP/WebSocket infrastructure and enabling direct process-based communication. Implements full MCP server semantics including resource listing, tool registration, and bidirectional message handling within a single TypeScript process.
Simpler deployment than HTTP-based MCP servers because it requires no port binding or network configuration; more efficient than REST wrappers because it uses MCP's native protocol; better integrated with Claude Desktop than generic GraphQL clients because it follows MCP conventions.
environment-driven configuration with fallback schema support
Medium confidenceImplements configuration management through environment variables (ENDPOINT, HEADERS, ALLOW_MUTATIONS, NAME, SCHEMA) that control server behavior at startup. The system supports a fallback mechanism where if a SCHEMA file path is provided, the server reads the local schema file instead of introspecting the live endpoint, enabling offline operation and schema caching. Headers are parsed from a JSON string in the HEADERS env var and injected into all GraphQL requests, supporting authentication tokens and custom headers without code changes.
Implements dual-mode schema loading: live introspection from endpoint OR local file fallback, allowing the same server binary to work offline or online. Uses JSON-parsed headers from env vars rather than individual header env vars, reducing configuration surface area.
More flexible than hardcoded configuration because it supports multiple deployment scenarios (live endpoint, cached schema, different auth methods); cleaner than config files because it integrates with standard container/cloud environment variable patterns; safer than CLI args because secrets aren't exposed in process listings.
mutation safety enforcement with explicit opt-in
Medium confidenceImplements a security control that blocks GraphQL mutation operations by default (ALLOW_MUTATIONS=false) and only allows them when explicitly enabled via environment variable. The server validates incoming GraphQL queries to detect mutation operations (queries containing 'mutation' keyword or mutation root types) and rejects them with an error message if mutations are disabled, preventing accidental or malicious data modification through LLM-generated queries.
Implements mutation blocking at the MCP server level rather than relying on endpoint-level permissions, providing a fail-safe control that works regardless of backend configuration. Uses explicit opt-in (ALLOW_MUTATIONS=true) rather than opt-out, defaulting to the safer posture.
More reliable than relying on GraphQL endpoint permissions because it blocks mutations before they reach the backend; simpler than role-based access control because it's a binary on/off switch; better for LLM safety because it prevents the LLM from even attempting mutations unless explicitly enabled.
request header injection with authentication support
Medium confidenceImplements a header injection mechanism that parses a JSON string from the HEADERS environment variable and injects those headers into every HTTP request sent to the GraphQL endpoint. This enables passing authentication tokens (Bearer tokens, API keys), custom headers (User-Agent, X-Custom-Header), and other request metadata without modifying the query execution logic. Headers are applied uniformly to all introspection and query execution requests.
Implements header injection via JSON-parsed environment variable rather than individual env vars per header, reducing configuration complexity. Headers are applied uniformly to all requests (introspection and queries) without requiring per-request customization.
Cleaner than passing headers as CLI arguments because secrets aren't exposed in process listings; more flexible than hardcoded auth because it supports any header type; simpler than implementing OAuth/OIDC because it works with any authentication scheme that uses HTTP headers.
graphql response error passthrough with full semantics
Medium confidenceImplements response handling that returns the complete GraphQL response object (including both 'data' and 'errors' fields) to the LLM, preserving GraphQL's native error semantics. When a GraphQL query returns errors (validation errors, resolver errors, authentication failures), the server passes the full error objects back to the LLM rather than throwing exceptions or flattening the response, allowing the LLM to reason about partial failures and retry logic.
Preserves GraphQL's native response semantics by returning both data and errors fields, rather than converting errors to exceptions or flattening responses. Allows LLMs to reason about partial failures and error types without additional parsing.
More informative than REST APIs that return HTTP status codes because GraphQL errors include structured error objects; more transparent than error-hiding wrappers because it exposes the full response; better for LLM reasoning because it preserves GraphQL's dual-field response model.
local schema file caching with sdl/json support
Medium confidenceImplements a schema fallback mechanism that reads GraphQL schema from a local file (specified via SCHEMA env var) instead of introspecting a live endpoint. The server supports both GraphQL SDL (Schema Definition Language) and JSON introspection format, allowing pre-cached schemas to be used for offline operation or to avoid repeated introspection calls. This enables the same server binary to work with cached schemas in development or when the endpoint is temporarily unavailable.
Implements dual-mode schema loading (live introspection OR local file) with automatic fallback, allowing the same server binary to work in multiple deployment scenarios. Supports both SDL and JSON introspection formats without requiring explicit format specification.
More flexible than endpoint-only introspection because it supports offline operation; simpler than schema registry solutions because it uses local files; better for version control than dynamic introspection because schemas can be committed to git.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
Related Artifactssharing capabilities
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@modelcontextprotocol/inspector-client
Client-side application for the Model Context Protocol inspector
@wong2/mcp-cli
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@modelcontextprotocol/inspector-server
Server-side application for the Model Context Protocol inspector
@mcp-contracts/cli
CLI tool for capturing and diffing MCP tool schemas
Best For
- ✓LLM application developers building agents that interact with GraphQL APIs
- ✓Teams integrating GraphQL backends with Claude/GPT via MCP
- ✓Developers wanting schema-aware code generation for GraphQL operations
- ✓LLM agents that need to fetch data from GraphQL APIs as part of reasoning/planning loops
- ✓Developers building retrieval-augmented generation (RAG) systems backed by GraphQL
- ✓Teams using LLMs to query complex data models exposed via GraphQL
- ✓Developers building Claude Desktop plugins or extensions
- ✓Teams deploying MCP servers in containerized environments (Docker, Kubernetes)
Known Limitations
- ⚠Schema is static at server startup — does not reflect real-time schema changes without server restart
- ⚠Introspection queries may timeout on very large schemas (100+ types with deep nesting)
- ⚠Local schema files must be manually kept in sync with actual endpoint schema
- ⚠Mutations are disabled by default (ALLOW_MUTATIONS=false) — requires explicit opt-in to prevent accidental data modification
- ⚠No built-in query complexity analysis — LLMs can construct expensive queries that timeout or consume excessive resources
- ⚠Variables must be passed as JSON; no support for file uploads or multipart requests
Requirements
Input / Output
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Repository Details
Last commit: Sep 8, 2025
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Model Context Protocol server for GraphQL
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