f2470f3e56
PeerCortex unifies PeeringDB, RIPE Stat, bgproutes.io, RIPE Atlas, Route Views, IRR, RPKI, and CAIDA into a single AI-queryable MCP Server for network engineers. Powered by local Ollama. Core capabilities: - 34 MCP tools for network intelligence - 11 data sources unified - ASPA validation engine (RFC 9582) with leak detection - Peering partner discovery with AI-ranked matches - BGP analysis and anomaly detection - RPKI monitoring and compliance reports - Latency/traceroute via RIPE Atlas - Transit analysis and cost comparison - IX traffic statistics - AS topology mapping - ASPA object generator and simulator - 100% local AI — no cloud dependencies
109 lines
2.4 KiB
Markdown
109 lines
2.4 KiB
Markdown
# Setup Guide
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## Prerequisites
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- **Node.js** 20+ (LTS recommended)
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- **Ollama** installed and running locally
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- **Docker** (optional, for containerized deployment)
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## Quick Start
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### 1. Install Ollama
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```bash
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# macOS
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brew install ollama
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# Linux
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curl -fsSL https://ollama.com/install.sh | sh
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# Pull a recommended model
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ollama pull llama3.1
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```
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### 2. Install PeerCortex
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```bash
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# Clone the repository
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git clone https://github.com/peercortex/peercortex.git
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cd peercortex
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# Install dependencies
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npm install
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# Copy environment configuration
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cp .env.example .env
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# Build
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npm run build
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# Start the MCP server
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npm start
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```
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### 3. Configure Claude Code
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Add PeerCortex to your Claude Code MCP configuration:
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```json
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{
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"mcpServers": {
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"peercortex": {
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"command": "node",
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"args": ["/path/to/peercortex/dist/mcp-server/index.js"],
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"env": {
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"OLLAMA_BASE_URL": "http://localhost:11434",
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"OLLAMA_MODEL": "llama3.1"
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}
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}
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}
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}
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```
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### 4. Docker Setup (Alternative)
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```bash
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# Start PeerCortex with Ollama
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docker compose up -d
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# Pull the AI model inside the Ollama container
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docker exec peercortex-ollama ollama pull llama3.1
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```
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## Configuration Reference
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See `.env.example` for all available configuration options.
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `OLLAMA_BASE_URL` | `http://localhost:11434` | Ollama API endpoint |
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| `OLLAMA_MODEL` | `llama3.1` | LLM model for analysis |
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| `PEERINGDB_API_KEY` | _(empty)_ | Optional PeeringDB API key |
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| `RIPE_STAT_SOURCE_APP` | `peercortex` | RIPE Stat source app identifier |
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| `ROUTINATOR_URL` | `http://localhost:8323` | Routinator RPKI validator URL |
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| `CACHE_DB_PATH` | `./peercortex-cache.db` | SQLite cache file path |
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| `CACHE_TTL_SECONDS` | `3600` | Default cache TTL |
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| `MCP_TRANSPORT` | `stdio` | Transport protocol (stdio/sse) |
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| `LOG_LEVEL` | `info` | Logging level |
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## Optional: PeeringDB API Key
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PeerCortex works without a PeeringDB API key, but you'll hit rate limits faster.
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To get a free API key:
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1. Create an account at [peeringdb.com](https://www.peeringdb.com/)
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2. Go to your profile settings
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3. Generate an API key
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4. Add it to your `.env` file
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## Optional: Local RPKI Validator
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For faster RPKI validation, run Routinator locally:
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```bash
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# Via Docker
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docker run -d --name routinator -p 8323:8323 nlnetlabs/routinator
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# Or uncomment the routinator service in docker-compose.yml
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```
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