Drop your PDFs, markdown, code, notebooks — **1800+ files, 39K chunks, indexed in under 3 minutes.**
Knowledge Rag MCP server exists for a simple reason — assistants are far more useful when they can act on Knowledge Rag directly instead of describing what you should do. Drop your PDFs, markdown, code, notebooks — 1800+ files, 39K chunks, indexed in under 3 minutes..
Once Knowledge Rag is connected, these are the calls the assistant has available:
v4.0.0 — Enterprise concurrent access: SSE/HTTP transport (1 server → N clients), thread-safe shared state, optional rate limiting + Prometheus metricsv3.9.0 — Quality Gate activated: 35+ automated PR checks across 7 pillars (Security, Stability, Memory Leak, Versatility, Scalability, Versioningv3.8.1 — Critical hotfix: loud-fail embeddings (no more silent zero-vector corruption); Windows CI flake erradicated (HF_HUB_OFFLINE + shell:bash + atexitv3.8.0 — Lazy-load embeddings, opt-in single-instance guard, version sync across PyPI/NPM/Dockerv3.6.0 — Multi-language code parsing (C/C++/JS/TS/XML), NPM wrapper, Docker image, automated release pipelinev3.5.2 — CUDA DLL auto-discovery from pip packages, graceful GPU→CPU fallback, explicit CPU provider (no CUDA noise when gpu: false), BASE_DIR resolution fixv3.5.1 — Remove Python <3.13 upper bound — 3.13 and 3.14 now supportedv3.5.0 — Optional GPU acceleration, supported formats table, full README rewritev3.4.3 — MCP stdout save/restore fix (v3.4.2 broke JSON-RPC responses)v3.4.0 — Persistent model cache, exclude patterns, Jupyter Notebook parser, inotify resilience, MetaTrader supportOptional — * NVIDIA GPU + CUDA 12 for accelerated embeddings (see GPU Acceleration below)Pillar — What it enforcesThe server ships on npm as knowledge-rag, 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.
You will need one environment variable: KNOWLEDGE_RAG_SINGLE_INSTANCE. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
This sits in the cloud and infrastructure group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Knowledge Rag's toolset — v4.0.0, v3.9.0, v3.8.1 and 11 more — is a fair guide to whether it matches your workflow. It is maintained by lyonzin; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Knowledge Rag's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| v4.0.0 | **Enterprise concurrent access**: SSE/HTTP transport (1 server → N clients), thread-safe shared state, optional rate limiting + Prometheus metrics, ChromaDB WAL mode, --transport CLI |
| v3.9.0 | **Quality Gate** activated: 35+ automated PR checks across 7 pillars (Security, Stability, Memory Leak, Versatility, Scalability, Versioning, Quality) + nightly resilience suite (chaos, soak, determinism, mutation) |
| v3.8.1 | Critical hotfix: loud-fail embeddings (no more silent zero-vector corruption); Windows CI flake erradicated (HF_HUB_OFFLINE + shell:bash + atexit wrapper) |
| v3.8.0 | Lazy-load embeddings, opt-in single-instance guard, version sync across PyPI/NPM/Docker |
| v3.6.0 | Multi-language code parsing (C/C++/JS/TS/XML), NPM wrapper, Docker image, automated release pipeline |
| v3.5.2 | CUDA DLL auto-discovery from pip packages, graceful GPU→CPU fallback, explicit CPU provider (no CUDA noise when gpu: false), BASE_DIR resolution fix for editable installs |
| v3.5.1 | Remove Python <3.13 upper bound — 3.13 and 3.14 now supported |
| v3.5.0 | Optional GPU acceleration, supported formats table, full README rewrite |
| v3.4.3 | MCP stdout save/restore fix (v3.4.2 broke JSON-RPC responses) |
| v3.4.0 | Persistent model cache, exclude patterns, Jupyter Notebook parser, inotify resilience, MetaTrader support |
| Optional | * NVIDIA GPU + CUDA 12 for accelerated embeddings (see [GPU Acceleration](#gpu-acceleration) below) |
| Pillar | What it enforces |
| Format | Extension |
| Markdown | .md |
{
"mcpServers": {
"knowledge-rag": {
"command": "npx",
"args": ["-y", "knowledge-rag"],
"env": {
"KNOWLEDGE_RAG_SINGLE_INSTANCE": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| KNOWLEDGE_RAG_SINGLE_INSTANCE | Configuration value read at startup. | Optional |
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