Server profile

CentralMind Gateway MCP Server

CentralMind Gateway exposes structured databases through MCP and REST APIs. It combines schema-based API generation with configurable security, PII redaction, caching, and request tracing for data-connected agents.

Server facts

CentralMind Gateway MCP Server

Project

License
Apache-2.0
Category
Databases

Tech

Runtime / language
goGo
Transports
stdio
Remote available
No
Authentication
Not specified

Activity

GitHub stars
547
Last commit
Data as of

Tags

  • Database Api
  • Observability
  • Openapi
  • Pii Redaction
  • Sql

Overview

CentralMind Gateway provides an API layer between structured databases and AI applications. It can expose data through MCP, including SSE, or through REST with generated Swagger documentation and an OpenAPI 3.1 specification. The README also describes direct SQL access. Supported databases include PostgreSQL, MySQL, ClickHouse, Snowflake, BigQuery, Oracle, SQLite, and other listed connectors. During discovery, a language model examines schema information and sampled data to produce an API configuration based on a prompt. The README explicitly limits this model use to discovery, separating API generation from the later serving stage. Developers can inspect the resulting YAML configuration before launching the API.

Security and operational features are configurable through plugins. The project describes API-key and OAuth options, sensitive-data redaction using regex or Microsoft Presidio, Lua-based row-level controls, and OpenTelemetry integration for tracing and auditing. Caching options include time-based and LRU strategies. Generation can use several hosted AI providers or configurable local model endpoints. Deployment choices include a binary, Docker, and Kubernetes, with a Docker quick start showing a PostgreSQL connection string and an SSE endpoint on port 9090. MCP methods come from the generated configuration, so the README does not establish a fixed tool catalog. Some authentication and write-related items also appear on the roadmap, making configuration review important rather than assuming every protection is enabled automatically.

Install & configure

Requirements

  • Docker
  • A reachable PostgreSQL database for this example
Documented launch / install command
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'

Replace the database connection placeholder. This README quick start exposes SSE at port 9090 and REST at the root. Custom discovery uses an AI provider and generates gateway.yaml; a separate stdio setup is also documented.

Config file · macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Windows: %APPDATA%\Claude\claude_desktop_config.json

Use Settings → Developer → Edit Config when available. Do not assume a Linux configuration path; check the client documentation for your platform. Remote servers use the app’s connector flow when supported, not the local stdio file shown here. Merge this example with existing settings; do not overwrite unrelated servers.

A supported configuration example is not available for this client and transport. Check the client documentation for its connection flow; do not substitute an undocumented JSON format.

Read the Claude Desktop setup guide

Config file · Project: .cursor/mcp.json

User: ~/.cursor/mcp.json

The project path is relative to the workspace root. The tilde denotes your user home directory. Use Cursor’s MCP settings to confirm which configuration and scope your installed version is reading. Merge this example with existing settings; do not overwrite unrelated servers.

Cursor configuration
{
  "mcpServers": {
    "gateway": {
      "url": "http://localhost:9090/sse"
    }
  }
}

Read the Cursor setup guide

Config file · Workspace: .vscode/mcp.json

For user scope, use the “MCP: Open User Configuration” command if available. Do not guess a user configuration path across operating systems, profiles, containers, or remote workspaces; check the client documentation. Merge this example with existing settings; do not overwrite unrelated servers.

A supported configuration example is not available for this client and transport. Check the client documentation for its connection flow; do not substitute an undocumented JSON format.

Read the VS Code setup guide

Config file · macOS/Linux: ~/.codeium/windsurf/mcp_config.json

Windows: %USERPROFILE%\.codeium\windsurf\mcp_config.json

Open the MCP configuration through Windsurf’s settings when possible to confirm the active file. Paths can differ in managed or future releases; check the client documentation if this location is not present. Merge this example with existing settings; do not overwrite unrelated servers.

Windsurf configuration
{
  "mcpServers": {
    "gateway": {
      "serverUrl": "http://localhost:9090/sse"
    }
  }
}

Read the Windsurf setup guide

Config file · Project scope: .mcp.json at the repository root

The project file uses mcpServers. For user scope, use claude mcp add --scope user rather than assuming .mcp.json in your home directory is the user configuration. Check the client documentation for managed settings and storage details. Merge this example with existing settings; do not overwrite unrelated servers.

Claude Code configuration
{
  "mcpServers": {
    "gateway": {
      "type": "sse",
      "url": "http://localhost:9090/sse"
    }
  }
}

Read the Claude Code setup guide

Examples are translated from the published configuration. Supply your own credentials and verify requirements in the upstream README. Remote connectors are shown only where a supported configuration format is known.

Tools

No individual tool names were confirmed in the source material. Check the repository for its current tool list.

Names, permissions, and defaults can change. Check the current upstream documentation before granting access.

Use cases

  • Expose a database to an assistant through MCP
  • Generate a REST API from schema and sampled data
  • Add configurable sensitive-data redaction to data access
  • Trace database-backed agent requests with OpenTelemetry

Strengths

  • Offers MCP and REST access from one API layer
  • Supports multiple structured database backends
  • Includes configurable redaction, row-level controls, and tracing

Limitations

  • API discovery requires a configured AI provider
  • Methods and protections depend on generated YAML and plugin configuration
  • Some security and write enhancements remain on the roadmap

Frequently asked questions

No. It also serves REST APIs with Swagger and OpenAPI 3.1 documentation.

The README states that an LLM generates the API configuration during discovery.

It documents regex and Microsoft Presidio plugins for sensitive-data redaction.

No fixed tool catalog is listed. MCP method names are part of the generated API configuration.

Independent listing, not an affiliation or security review. Grant the least access needed and verify the upstream instructions before running code.

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