# agentic-rag-knowledge-assistant

> agentic-rag-knowledge-assistant — jayanthlocam-agentic-rag-postgres-mcp. Use this tool when you need to securely ingest and retrieve documents, or perform vector searches on PDF, DOCX, and text files. It solves problems related to document management and semantic search, providing authenticated access to stored knowledge through MCP tools. The tool accepts document files as input and returns relevant search results, enabling efficient information retrieval in tenant-isolated environments.

Canonical page: https://skillsregistry.net/skills/jayanthlocam-agentic-rag-postgres-mcp  
JSON: https://api.skillsregistry.net/v1/skills/jayanthlocam-agentic-rag-postgres-mcp

## Description

Agentic RAG Knowledge Assistant is a secure, tenant-isolated MCP server built with FastAPI, PostgreSQL, and pgvector that enables document ingestion, semantic retrieval, and vector search over PDF, DOCX, and text files through authenticated MCP tools.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/t2lmh2z236)
- **Repository:** <https://github.com/jayanthlocam/agentic-rag-postgres-mcp>

## 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": "jayanthlocam-agentic-rag-postgres-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jayanthlocam-agentic-rag-postgres-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jayanthlocam-agentic-rag-postgres-mcp/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