1. **Scan** 500MB+ files in seconds using ripgrep 2. **Parse** error patterns, deduplicate repeated events 3. **Analyse** using local LLM (Ollama +
The server publishes 3 tools. What each one is for:
ping — The ping tool exposed by this serveranalyze_log_file — Start async log analysis. Returns a job ID immediately — pipeline runs in backgroundget_job_status — The get_job_status tool exposed by this serverThe server ships on PyPI as mcp, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
Configuration is passed through the environment: GITHUB_PAT, GITHUB_REPO_OWNER, GITHUB_REPO_NAME, OLLAMA_BASE_URL, OLLAMA_MODEL. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
| Requirement | Version | Notes | |---|---|---| | Python | 3.11+ | 3.14 not supported | | Ollama | Latest | brew install ollama | | deepseek-r1:14b | — | ~9GB download | | ripgrep | Latest | brew install ripgrep | | RAM | 16GB min | 32GB recommended | | macOS | Ventura 13+ | Apple Silicon recommended | ---
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Nft Log Analyzer's toolset — ping, analyze_log_file, get_job_status — is a fair guide to whether it matches your workflow. It is maintained by mashish; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Nft Log Analyzer's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| ping | The ping tool exposed by this server. |
| analyze_log_file | Start async log analysis. Returns a job ID immediately — pipeline runs in background. |
| get_job_status | The get_job_status tool exposed by this server. |
{
"mcpServers": {
"nft-log-analyzer": {
"command": "uvx",
"args": ["mcp"],
"env": {
"GITHUB_PAT": "your-value",
"GITHUB_REPO_OWNER": "your-value",
"GITHUB_REPO_NAME": "your-value",
"OLLAMA_BASE_URL": "your-value",
"OLLAMA_MODEL": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Requirement | Version | Notes | |---|---|---| | Python | 3.11+ | 3.14 not supported | | Ollama | Latest | brew install ollama | | deepseek-r1:14b | — | ~9GB download | | ripgrep | Latest | brew install ripgrep | | RAM | 16GB min | 32GB recommended | | macOS | Ventura 13+ | Apple Silicon recommended | ---
| Variable | Description | Required |
|---|---|---|
| GITHUB_PAT | Configuration value read at startup. | Optional |
| GITHUB_REPO_OWNER | Configuration value read at startup. | Optional |
| GITHUB_REPO_NAME | Configuration value read at startup. | Optional |
| OLLAMA_BASE_URL | Endpoint or connection string the server talks to. | Yes |
| OLLAMA_MODEL | Configuration value read at startup. | Optional |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.