phpMyFAQ
phpMyFAQ - Open Source FAQ web application for PHP 8.3+ and MySQL, PostgreSQL and other databases
claude mcp add --transport stdio thorsten-phpmyfaq docker run -i thorsten/phpmyfaq:latest \ --env PHPMYFAQ_DB_HOST="your-database-host" \ --env PHPMYFAQ_DB_NAME="your-database-name" \ --env PHPMYFAQ_DB_USER="your-database-user" \ --env PHPMYFAQ_APP_PORT="8080" \ --env PHPMYFAQ_DB_PASSWORD="your-database-password" \ --env PHPMYFAQ_ELASTICSEARCH_HOST="http://localhost:9200"
How to use
phpMyFAQ is a multilingual, AI-ready, and scalable FAQ platform powered by PHP 8.4+ that can be deployed locally or in the cloud. When run via Docker, you typically mount the phpMyFAQ source folder into the container and expose a web server interface for setup and usage. The server provides a REST API, supports Elasticsearch/OpenSearch for enhanced search capabilities, and includes enterprise authentication options (LDAP, Active Directory, Entra ID). Use the included Docker setup to spin up a multi-container environment with databases, search engines, and web servers, enabling you to develop, test, and run phpMyFAQ in a contained environment. The tools available include a web-based admin interface, REST API endpoints for content and user management, and optional search integration with Elasticsearch/OpenSearch for improved querying and relevancy.
To interact with the MCP server, start the Docker-based phpMyFAQ stack, ensure the database and search services are reachable, and access the web UI to perform installation, configuration, and content management. If you enable the REST API, you can programmatically manage FAQs, categories, users, and permissions, as well as perform search queries against your indexed content.
How to install
Prerequisites:
- Docker and docker-compose installed on your host
- Git installed to clone repositories (optional if using direct image)
Installation steps:
- Clone or download the phpMyFAQ repository that you want to run locally.
- Ensure you have a database instance ready (MySQL/MariaDB, PostgreSQL, etc.) and note the connection details.
- Create a docker-compose.yml (or adapt the one provided in the repo) to wire phpMyFAQ with its database and optional Elasticsearch/OpenSearch instance. For a quick start, you can build a minimal stack with a PHP-enabled web server and a database.
- Start the stack:
- Using Docker run command (example):
docker run -d --name phpmyfaq -p 8080:80
-e PHPMYFAQ_DB_HOST=your-db-host
-e PHPMYFAQ_DB_NAME=your-db-name
-e PHPMYFAQ_DB_USER=your-db-user
-e PHPMYFAQ_DB_PASSWORD=your-db-password
thorsten/phpmyfaq:latest - Or using docker-compose if provided by the repo: docker-compose up -d
- Using Docker run command (example):
docker run -d --name phpmyfaq -p 8080:80
- Open http://localhost:8080/setup/ in your browser to complete the installation and configuration through the web UI.
- If you enable Elasticsearch/OpenSearch, ensure the service is running and reachable at the configured host/port.
Note: The Dockerfile in the repository is intended for development purposes and does not contain the application code itself; you typically mount the phpMyFAQ code into the container or use an image that already contains the application.
Additional notes
Tips and common issues:
- Ensure vm.max_map_count is set to at least 262144 if using Elasticsearch/OpenSearch in your stack (per Elasticsearch requirements).
- If you’re using Docker for Mac/Windows, adjust resource allocations (CPU/RAM) to meet the needs of the stack, especially when running multiple containers like DBs and search engines.
- The REST API documentation for phpMyFAQ is available in the repo/docs and OpenAPI specs; use them to interact programmatically with the FAQ data.
- When mounting the local phpMyFAQ source, ensure proper permissions for the container to read/write to the mounted folder.
- If you plan to run tests, install development dependencies (Composer for PHP, Node tooling if you build frontend assets) as described in the repo’s testing instructions.
Related MCP Servers
netdata
The fastest path to AI-powered full stack observability, even for lean teams.
mcpcan
MCPCAN is a centralized management platform for MCP services. It deploys each MCP service using a container deployment method. The platform supports container monitoring and MCP service token verification, solving security risks and enabling rapid deployment of MCP services. It uses SSE, STDIO, and STREAMABLEHTTP access protocols to deploy MCP。
agentscope-runtime
A production-ready runtime framework for agent apps with secure tool sandboxing, Agent-as-a-Service APIs, scalable deployment, full-stack observability, and broad framework compatibility.
mcp-for-argocd
An implementation of Model Context Protocol (MCP) server for Argo CD.
magg
Magg: The MCP Aggregator
nestjs-starter
Production-ready NestJS boilerplate with JWT auth, PostgreSQL/Prisma, AWS S3/SES, Bull/Redis queues, Docker/K8s support, and MCP integration for AI capabilities