MCP Graphql Enhanced

mcp-graphql-enhanced

An enhanced MCP (Model Context Protocol) server for GraphQL that fixes real-world interoperability issues between LLMs and GraphQL APIs.

Drop-in replacement for mcp-graphql — with dynamic headers, robust variables parsing, and zero breaking changes.

🎯 What is mcp-graphql-enhanced?

mcp-graphql-enhanced is a high-performance, federated GraphQL gateway designed to act as a workhorse for LLM agents. It bridges the gap between massive, complex GraphQL ecosystems and the context-limited environment of AI assistants. Unlike standard "all-or-nothing" introspection tools that crash under the weight of large schemas (like GitHub's or enterprise-grade Neo4j graphs), this server provides surgical control over how your agent perceives and interacts with your data.

💡 Why do you need it?

If you have ever seen the Tool result is too large while trying to introspect your API, you are already hitting the limits of standard MCP implementations. Here is why mcp-graphql-enhanced is a practical choice for professional environments:

Avoid the 1MB Ceiling: It shifts the responsibility for scope from the server to the caller. Instead of a unilateral "everything or nothing" dump, you get granular control via typeNames and typeDepth parameters.

Surgical Precision: You can selectively introspect only the nodes you need (e.g., Repository, User, or Message), keeping your context window clean and your LLM focused.

Predictability over Immunity: It doesn't promise "unlimited" capacity—it promises predictability. In enterprise systems, you need a tool that lets you navigate the graph surgically and fail predictably if you overstep, rather than a "black box" that dies on you the moment the schema grows.

Demonstration: See a real-world diagnostic test against the GitHub API that compares scoped and monolithic introspection: 🔗 Diagnostic Case Study: Scoped vs. Monolithic Introspection (Shared Chat)

💬 Community & Support

Join the conversation! If you have questions about using this bridge with Neo4j, Discord data graphs, or GraphQL in general, come hang out with us:

• Discord Channel: #mcp-graphql-enhanced
• Server: The official GraphQL Discord

This is the best place to share your feedback, report issues, or suggest new "enhanced" features for the bridge.

✨ Key Enhancements

• ✅ Dynamic Endpoint Switching — Hot-swap targets on the fly directly via tool arguments without restarting the server or losing session context.
• ✅ Built-in GraphiQL IDE — Visual playground at / (or /graphql, /graphiql) with pre-configured headers for instant testing and introspection.
• ✅ Dual Transport — Supports both STDIO (for local CLI/client tools) and HTTP/JSON-RPC (for external/browser clients).
• ✅ Dynamic headers — pass Authorization, X-API-Key, etc., via tool arguments (no config restarts)
• ✅ Robust variables parsing — fixes “Query variables must be a null or an object” error
• ✅ Smart introspection — supports filtered requests (via typeNames) and recursive depth control (via typeDepth) to minimize LLM context noise and optimize schema exploration.
• ✅ Full MCP compatibility — works with Claude Desktop, Groq Desktop, Google Antigravity, Glama, Gemini CLI, Hermes Agent and any standard MCP client
• ✅ Secure by default — mutations disabled unless explicitly enabled
• ✅ Dynamic Schema Evolution — Smart diagnostics and gap analysis for servers that regenerate GraphQL types on-the-fly (like Neo4j).
• ✅ Deep Observability — Automatic Cypher extraction and cleaning from GraphQL extensions.

🔥 Dynamic Endpoint Switching

The bridge allows LLMs or clients to dynamically target different GraphQL endpoints at runtime within a single session without requiring server restarts or configuration changes.

Simply pass the optional endpoint parameter in query-graphql or introspect-schema:

• Zero Downtime: Hot-swaps the underlying schema and clears internal caches instantly.
• Context Preservation: Keeps the MCP connection open while shifting queries between different environments (e.g., switching from a Discord ingest node to a Neo4j graph database).

🚀 Federated Multi-Node Architecture (since v3.9.1)

The server operates as a Federated GraphQL Gateway capable of querying multiple independent GraphQL environments through a single endpoint.

• Zero Breaking Changes: If you provide a single URL in ENDPOINT, the server behaves exactly as before.

• Federated Capability Discovery: During startup, all configured endpoints are introspected to build a federated manifest used for routing, relevance analysis, and node selection.

• Stable Runtime Introspection: Direct GraphQL introspection queries (__schema, __type) are always resolved against the first configured endpoint. This preserves a consistent schema model and avoids corruption caused by merging independent introspection trees.

• Selective Node Routing: The federated manifest is consulted before execution to determine whether a query is relevant to a node, reducing unnecessary requests and improving performance.

• Schema-Adaptive Broadcasts: Queries are automatically pruned against each participating schema before execution. Unsupported fields and empty selection branches are removed on a per-node basis, allowing a single query to operate across heterogeneous GraphQL environments.

• Smart Aggregation: When multiple comma-separated URLs are provided, the server broadcasts queries, aggregates responses, and performs universal deep object-level deduplication.

• Conflict Handling: Structural differences between identically named types across nodes are detected and exposed safely.

• Unified Graph Experience: Independent GraphQL systems can be queried through a single endpoint, including combinations such as GitHub GraphQL, Neo4j GraphQL, and custom GraphQL APIs.

• Bypass Free Tier Limits: Useful for Free Tier cloud databases (for example Neo4j Aura). Data can be distributed across multiple instances while remaining queryable through a single federated gateway.

Proof of Concept:

See a real-world demonstration of the federated query synthesis in action, where the agent aggregates live Discord data with historical Neo4j insights: 🔗 Live Federation Analysis (Shared Chat)

💡 Use Case: Bridging WSL and Windows (PowerShell)

A common challenge for Windows developers is the network isolation between the Windows Subsystem for Linux (WSL) and the host OS. This feature allows you to bridge these two worlds into a "Unified Nervous System".

Example configuration for Claude Desktop:

{

"ENDPOINT": "http://DESKTOP-NAME.local:2311/graphql,http://127.0.0.1:4000/graphql" }

*   **Hybrid Ecosystem**: Seamlessly query and aggregate data across Windows-native processes (PowerShell) and Linux-based environments (WSL).  

• mDNS Support: By using .local addresses, the bridge automatically resolves the host machine's IP from within the WSL environment.

• Transparent Aggregation: The AI assistant interacts with a single unified schema, unaware that the data is being fetched from different operating systems simultaneously.

🔍 Advanced Observability & Cypher

The bridge provides deep insights into how the LLM interacts with your graph database.

🕸️ Automated Cypher Extraction

For GraphQL server implementations that return query execution plans (like @neo4j/graphql), the bridge automatically:

1. Detects extensions.cypher in the response.
2. Sanitizes the output by stripping internal headers (like CYPHER 5 or empty PARAMS).
3. Injects a clean Cypher block directly into the tool's output for the AI to analyze.

Note: This feature requires your GraphQL server to be configured to include debug information in the response extensions.

🎨 Visual Command Center (GraphiQL)

Unlike standard MCP servers, this one provides a visual interface for humans. When running with ENABLE_HTTP=true, you can open a full-featured GraphiQL IDE in your browser.

• Endpoint: http://localhost:6274/ (or /graphql, /graphiql)
• Header Sync: Any headers set in your environment (like GitHub tokens) are automatically injected into the GraphiQL "Headers" tab for immediate testing.

💻 HTTP / Dual Transport

This server runs in dual transport mode, supporting both the standard STDIO communication (used by most MCP clients) and an HTTP JSON-RPC endpoint on port 6274.

This allows external systems, web applications, and direct curl commands to access the server's tools with live request logging in your terminal ([HTTP-RPC] logs).

Resolving Port Conflicts (EADDRINUSE) and Automatic Port Selection

The server defaults to port 6274. If you encounter an EADDRINUSE: address already in use :::6274 error (common in local development due to stale processes), the server will automatically find the next available port (up to 10 attempts, not spawning multiple servers).

This ensures the server starts successfully even when the default is blocked. Always check the server logs for the final bound port (e.g., [HTTP] Started server on http://localhost:6275) if your curl or client tool fails on the default 6274.

To force a specific port (e.g., for guaranteed external firewall settings), you can still explicitly set the MCP_PORT environment variable:

MCP_PORT=8080 npx @letoribo/mcp-graphql-enhanced

Testing the HTTP Endpoint

You can test the endpoint using curl as long as the server is running (e.g., via npm run dev):

Test the health check (assuming the server bound to the default or found the next available port)

curl http://localhost:6274/health

Testing the JSON-RPC Transport

curl -X POST http://localhost:6274/mcp  \

-H "Content-Type: application/json" \ -d '{ "jsonrpc":"2.0", "method":"tools/list", "params":{}, "id":1 }'

curl -X POST http://localhost:6274/mcp \ -H "Content-Type: application/json" \ -d '{ "jsonrpc": "2.0", "method": "tools/call", "params": { "name": "introspect-schema", "arguments": {} }, "id": 2 }'

curl -X POST http://localhost:6274/mcp \ -H "Content-Type: application/json" \ -d '{ "jsonrpc": "2.0", "method": "tools/call", "params": { "name": "introspect-schema", "