NeuralLog Server
@NeuralLog
About NeuralLog Server
Central logging server for the AI-MCP-Logger ecosystem
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"server-neurallog": {
"command": "docker",
"args": [
"build",
"-t",
"neurallog-server",
"."
]
}
}
}Tools
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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
FAQ from NeuralLog Server
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.
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.
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.
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.
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.
Frequently asked questions
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.
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.
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.
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`.
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.
Basic information
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