VelociRAG MCP
A community-built MCP server providing lightning-fast Retrieval-Augmented Generation for AI agents. It utilizes ONNX Runtime for local inference without PyTorch or GPUs, offering four-layer retrieval fusion including vector similarity, BM25, knowledge graph traversal, and metadata filtering. It supports Unix socket daemons for warm queries and integrates with agents like Claude Code and Cursor.
Package and access
Local package with source-attributed installation metadata. Koskamo does not execute packages during review.
What you can do with it
- Index local documents for semantic search
- Perform multi-layer retrieval fusion (vector, BM25, KG)
- Integrate RAG capabilities into Claude Code or Cursor
- Run local AI inference without GPU dependencies
Source and maintenance
- Maintenance checked
Packages and installation
Source-provided package data. Koskamo has not executed or live-probed this package.
velocirag 0.7.4
{
"version": "0.7.4",
"transport": "stdio",
"identifier": "velocirag",
"registryType": "pypi",
"registryBaseUrl": "https://pypi.org"
}Tools
Reported by the attributed source; not independently observed by Koskamo.
Connect from your client
Each snippet configures the same source-provided package; replace placeholders before use.
Cursor
{
"mcpServers": {
"velocirag-mcp": {
"command": "uvx",
"args": [
"velocirag==0.7.4"
]
}
}
}Cline
{
"mcpServers": {
"velocirag-mcp": {
"command": "uvx",
"args": [
"velocirag==0.7.4"
]
}
}
}VS Code
{
"servers": {
"velocirag-mcp": {
"type": "stdio",
"command": "uvx",
"args": [
"velocirag==0.7.4"
]
}
}
}Claude Desktop
{
"mcpServers": {
"velocirag-mcp": {
"command": "uvx",
"args": [
"velocirag==0.7.4"
]
}
}
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