
π§ MCP Servers
A curated collection of custom MCP (Model Context Protocol) servers for internal use.
These servers expose specific toolsets (like browser automation or database interaction) via a natural language interface using the MCP protocol.
π¦ Included Servers
-
Puppeteer
Natural language interface to control automated browsers using Puppeteer and Chrome/Browserless. -
Postgres Vector Store
Interface to search and interact with a PostgreSQL-backed vector database. -
MySQL
Allows users to query and interact with a MySQL database using natural language prompts. -
Parquet (in progress)
Experimental server that converts between JSON and Parquet formats using natural language instructions.
π Easy Integration with Clients (Claude, Cursor, etc.)
MCP servers integrate natively with clients like Claude, Cursor, and other MCP-compatible tools.
Just point the client to your MCP server by adding it to your configuration file like this:
After server is running:
{
"mcpServers": {
"puppeteer": {
"type": "sse",
"url": "http://localhost:8000/sse"
},
"pgvector": {
"type": "sse",
"url": "http://localhost:8001/sse"
},
"mysql": {
"type": "sse",
"url": "http://localhost:8002/sse"
}
}
}This makes your server instantly accessible to tools capable of understanding the MCP protocol.
π Official MCP Documentation
π License
This project is licensed under the MIT License.
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~π Getting Started
Clone and build:
# 1 - clone this repo
git clone https://github.com/mend3/mcp
# 2 - that will create a folder called "mcp" on your current directory
# with that in mind, you can just attach the docker-compose
docker compose up \
# your docker-compose
-f docker-compose.yml \
# mcp docker-compose
-f mcp/docker-compose.yml \
build mcp-*Start all MCP servers using Docker Compose:
docker compose up -d mcp-*Run a specific server locally (in development mode):
tsx src/[server]Replace [server] with the desired module (e.g., puppeteer, mysql, pgvector).
No common issues documented yet. If you hit a problem, the repository's GitHub Issues page is the best place to look.