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NeuralLog Server MCP Server

@NeuralLog

Repository

Basic information

Category

Other

Transports

stdio

Author

NeuralLog

About NeuralLog Server MCP Server

Central logging server for the AI-MCP-Logger ecosystem

NeuralLog Server MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "server-neurallog": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "neurallog-server",
        "."
      ]
    }
  }
}

NeuralLog Server MCP Server 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 NeuralLog Server?

NeuralLog Server is the central server component of the NeuralLog intelligent logging system. It provides RESTful APIs for log management and storage, and supports the MCP (Model Context Protocol) ecosystem. It is designed for developers and operators who need to capture log events, analyze patterns, and trigger configurable actions.

How to use NeuralLog Server?

Deploy using Docker Compose with one of three storage adapters: Memory (development/testing), NeDB (small-scale), or Redis (production recommended). Use commands like docker-compose -f docker-compose.redis.yml up -d or the equivalent npm script. Configure storage via the STORAGE_TYPE environment variable. The server can also be deployed to Kubernetes using provided k8s manifests. Access the REST API at the configured port (default 3030 for Redis, 3031 for NeDB, 3032 for Memory).

Key features of NeuralLog Server

  • RESTful API for log management and retrieval
  • Support for Memory, NeDB, and Redis storage adapters
  • Namespace support for logical data isolation
  • Persistent storage with Docker volumes
  • Comprehensive search capabilities and statistics tracking
  • MCP client integration and multi-tenant support
  • Kubernetes deployment support with ConfigMaps and Secrets

Use cases of NeuralLog Server

  • Centralized log aggregation from multiple applications
  • Search and analysis of log events with filtering criteria
  • Integration with MCP clients (TypeScript, Unity, Python)
  • Multi-tenant log management using namespaces
  • Production-scale logging with Redis-backed persistent storage

Frequently asked questions

1

What storage backends are available?

Memory (data lost on restart), NeDB (file-based, small-scale), and Redis (production recommended). Configure via `STORAGE_TYPE` environment variable.

2

How do I run the server with persistent data?

Use Docker Compose with NeDB (`docker-compose -f docker-compose.nedb.yml up -d`) or Redis (`docker-compose -f docker-compose.redis.yml up -d`). Data is stored in Docker volumes.

3

What ports does the server use?

Redis storage: 3030; NeDB storage: 3031; Memory storage: 3032. The port can be changed with the `PORT` environment variable.

4

Can I deploy NeuralLog Server on Kubernetes?

Yes, use the provided k8s configuration files with `kubectl apply -k k8s`. An Ingress is configured at `http://neurallog.local`.

5

How do I test the server end-to-end?

Run the built-in end-to-end tests with `npm run test:e2e`, which starts the server via Docker Compose, runs a client, and cleans up. Manual testing with curl is also documented.

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