Columbia MCP Servers

@MCP-Mirror

Repository

Basic information

About Columbia MCP Servers

Mirror of

#mcp #servers #docker #monitoring

Columbia MCP Servers config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Columbia MCP Servers tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Columbia MCP Servers?

This repository provides the deployment infrastructure and server implementations for Columbia's Model Context Protocol (MCP) servers. It includes Docker‑based deployment, monitoring, and security tooling for a collection of AI, data, and tool services.

How to use Columbia MCP Servers?

Clone the repository, run the setup script (setup.sh), configure the .env file, and then deploy with deploy.sh. Monitoring can be started via monitor.sh. The server is designed for production use with containerized services.

Key features of Columbia MCP Servers

Docker‑based deployment with Docker Compose
High availability via load balancing and replication
Prometheus and Grafana monitoring integration
SSL/TLS, authentication, and rate limiting security
Horizontal scaling capabilities
Automated backup with point‑in‑time recovery

Use cases of Columbia MCP Servers

Deploying MCP services in a production environment
Monitoring service health and metrics with Prometheus and Grafana
Managing AI, data, and tool services as a unified stack
Implementing a secure, scalable MCP server infrastructure
Automating backup and disaster recovery

Frequently asked questions

What are the system requirements?

Docker 20.10+, Docker Compose 2.0+, Node.js 18+, and Redis 6+ are required.

How do I deploy Columbia MCP Servers?

Clone the repository, run `setup.sh`, edit the `.env` file, and then execute `deploy.sh`. Use `monitor.sh` to check health and metrics.

What monitoring tools are included?

Prometheus (port 9090) and Grafana (port 3000) are integrated for metrics collection and visualization.

How is security implemented?

Services run in isolated containers with SSL/TLS encryption, Redis password protection, rate limiting, and regular security updates.

What types of services are provided?

The repository includes implementations for AI‑related services, data services, and tool services under the `services/` directory.

Comments

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