# KBDB

> Use this tool when you need to perform semantic search across large document collections, solving problems like knowledge base querying, documentation search, and content discovery. It takes in natural language queries and document embeddings as inputs, and outputs relevant search results based on various similarity metrics, including cosine, inner product, and L2 distance. Ideal for applications requiring advanced semantic matching, such as question-answer pairs, style-based clustering, and code similarity search.

Canonical page: https://skillsregistry.net/skills/luxter77-kbdb  
JSON: https://api.skillsregistry.net/v1/skills/luxter77-kbdb

## Description

A PostgreSQL-backed RAG (Retrieval-Augmented Generation) server that provides semantic search across document embeddings using pgvector for vector similarity operations. Built with FastMCP and OpenAI's embedding API, it supports multiple search modalities including question-answer pairs, semantic similarity, style-based clustering, and code similarity search, each optimized with different embedding prefixes and distance metrics (cosine, inner product, L2). The system stores documents in chunks with pre-computed embeddings and exposes specialized search tools for different use cases, making it valuable for knowledge base applications, documentation search, and content discovery workflows where different types of semantic matching are required.

## Trust

- **Trust score (0–1):** 0.93
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/luxter77-kbdb)
- **Repository:** <https://github.com/luxter77/mcp-kbdb>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "luxter77-kbdb"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/luxter77-kbdb` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/luxter77-kbdb/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt