CentralMind Gateway

by centralmind

CentralMind Gateway 是一款通过 MCP 或 OpenAPI 3.1 协议将您的数据库暴露给 AI 代理的工具。它支持多种结构化数据库,并提供针对 AI 工作负载优化的 API。配置通过 YAML 文件(如 gateway.yaml)完成,文件在发现过程中生成。

Developer toolsstdioCommunity

Repository-wide counts · Cached 2026-03-07

Overview

The CentralMind Gateway MCP server is a publicly available project. Review the upstream repository for installation instructions, supported tools, compatibility, permissions, and current maintenance status.

Configuration

Configuration, transport, authentication, and runtime requirements vary by project. Open the repository before connecting and use the smallest set of credentials and permissions required.

Open the CentralMind Gateway repository to read the latest documentation.

KEEP EXPLORING

Compare source, connection, and authentication details before choosing an implementation.

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FROM THE SOURCE

Repository README

Build-time snapshot · Retrieved 2026-10-05

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Build Binaries           

CentralMind Gateway: Create API or MCP Server in Minutes

🚀 Interactive Demo avialable here: https://centralmind.ai

What is Centralmind/Gateway

Simple way to expose your database to AI-Agent via MCP or OpenAPI 3.1 protocols.

docker run --platform linux/amd64 -p 9090:9090 \
  ghcr.io/centralmind/gateway:v0.2.18 start \
  --connection-string "postgres://db-user:db-password@db-host/db-name?sslmode=require"

This will run for you an API:

INFO Gateway server started successfully!         
INFO MCP SSE server for AI agents is running at: http://localhost:9090/sse 
INFO REST API with Swagger UI is available at: http://localhost:9090/ 

Which you can use inside your AI Agent:

mcp-raw-cursor-setup.png

Gateway will generate AI optimized API.

Why Centralmind/Gateway

AI agents and LLM-powered applications need fast, secure access to data. We're building an API layer that automatically generates secure, LLM-optimized APIs for your structured data.

  • Quickly start with MCP or OpenAPI, or use Direct/Raw SQL APIs
  • Filters out PII and sensitive data to ensure compliance with GDPR, CPRA, SOC 2, and other regulations
  • Adds traceability and auditing capabilities, ensuring AI applications aren't black boxes and allowing security teams to maintain control
  • Optimized for AI workloads: supports the Model Context Protocol (MCP) with enhanced metadata to help AI agents understand APIs, along with built-in caching and security features

It can be useful during development, when an LLM needs to create, adjust, or query data from your database. In analytical scenarios, it enables you to chat with your database or data warehouse. Enrich your AI agents with data from your database using remote function/tool calling.

demo

Features

How it Works

img.png

1. Connect & Discover

Gateway connects to your structured databases like PostgreSQL and automatically analyzes the schema and data samples to generate an optimized API structure based on your prompt. LLM is used only on discovery stage to produce API configuration. The tool uses AI Providers to generate the API configuration while ensuring security through PII detection.

2. Deploy

Gateway supports multiple deployment options from standalone binary, docker or Kubernetes. Check our launching guide for detailed instructions. The system uses YAML configuration and plugins for easy customization.

3. Use & Integrate

Access your data through REST APIs or Model Context Protocol (MCP) with built-in security features. Gateway seamlessly integrates with AI models and applications like LangChain, OpenAI and Claude Desktop using function calling or Cursor through MCP. You can also setup telemetry to local or remote destination in otel format.

Documentation

Getting Started

Additional Resources

How to Build

# Clone the repository
git clone https://github.com/centralmind/gateway.git

# Navigate to project directory
cd gateway

# Install dependencies
go mod download

# Build the project
go build .

API Generation

Gateway uses LLM models to generate your API configuration. Follow these steps:

Choose one of our supported AI providers:

Google Gemini provides a generous free tier. You can obtain an API key by visiting Google AI Studio:

Once logged in, you can create an API key in the API section of AI Studio. The free tier includes a generous monthly token allocation, making it accessible for development and testing purposes.

Configure AI provider authorization. For Google Gemini, set an API key.

export GEMINI_API_KEY='yourkey'
  1. Run the discovery command:
./gateway discover \
  --ai-provider gemini \
  --connection-string "postgresql://neondb_owner:MY_PASSWORD@MY_HOST.neon.tech/neondb?sslmode=require" \
  --prompt "Generate for me awesome readonly API"
  1. Enjoy the generation process:
INFO 🚀 API Discovery Process
INFO Step 1: Read configs
INFO ✅ Step 1 completed. Done.

INFO Step 2: Discover data
INFO Discovered Tables:
INFO   - payment_dim: 3 columns, 39 rows
INFO   - fact_table: 9 columns, 1000000 rows
INFO ✅ Step 2 completed. Done.

# Additional steps and output...

INFO ✅ All steps completed. Done.

INFO --- Execution Statistics ---
INFO Total time taken: 1m10s
INFO Tokens used: 16543 (Estimated cost: $0.0616)
INFO Tables processed: 6
INFO API methods created: 18
INFO Total number of columns with PII data: 2
  1. Review the generated configuration in gateway.yaml:
api:
  name: Awesome Readonly API
  description: ''
  version: '1.0'
database:
  type: postgres
  connection: YOUR_CONNECTION_INFO
  tables:
    - name: payment_dim
      columns: # Table columns
      endpoints:
        - http_method: GET
          http_path: /some_path
          mcp_method: some_method
          summary: Some readable summary
          description: 'Some description'
          query: SQL Query with params
          params: # Query parameters

Running the API

Run locally

./gateway start --config gateway.yaml

Docker Compose

docker compose -f ./example/simple/docker-compose.yml up

MCP Protocol Integration

Gateway implements the MCP protocol for seamless integration with Claude and other tools. For detailed setup instructions, see our Claude integration guide.

To add MCP Tool to Claude Desktop just adjust Claude's config :

{
  "mcpServers": {
    "gateway": {
      "command": "PATH_TO_GATEWAY_BINARY",
      "args": ["start", "--config", "PATH_TO_GATEWAY_YAML_CONFIG", "mcp-stdio"]
    }
  }
}

Roadmap

It is always subject to change, and the roadmap will highly depend on user feedback. At this moment, we are planning the following features:

Database and Connectivity
  • 🗄️ Extended Database Integrations - Databricks, Redshift, S3 (Iceberg and Parquet), Oracle DB, Microsoft SQL Server, Elasticsearch
  • 🔑 SSH tunneling - ability to use jumphost or ssh bastion to tunnel connections
Enhanced Functionality
  • 🔍 Advanced Query Capabilities - Complex filtering syntax and Aggregation functions as parameters
  • 🔐 Enhanced MCP Security - API key and OAuth authentication
Platform Improvements
  • 📦 Schema Management - Automated schema evolution and API versioning
  • 🚦 Advanced Traffic Management - Intelligent rate limiting, Request throttling
  • ✍️ Write Operations Support - Insert, Update operations

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