mcp-rag-assistant

MCP server that provides 8 local RAG tools using LlamaIndex and Ollama, enabling AI-powered document querying, summarization, analysis, and comparison over PDFs, DOCX, XLSX, and CSV files.

→ Hassan-Butt4356/mcp-rag-assistant · listed on glama

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// key findings

✅

No credential exfiltration, no sensitive file access, no obfuscation

Static analysis found nothing flowing your secrets to unexpected places.

// required environment variables

This server reads these from process.env. You'll be asked to provide them before it can run.

configOLLAMA_BASE_URL

configLLM_MODEL— mistral:latest

configFALLBACK_MODEL

configEMBED_MODEL— nomic-embed-text:latest

configCHUNK_SIZE— 256 Tokens per chunk. Smaller = more precise retrieval

configCHUNK_OVERLAP— 25 Overlap between chunks. Helps preserve context at boundaries

configSIMILARITY_TOP_K— 5 Chunks retrieved per query

configRERANK_TOP_N

configRESPONSE_MODE— compact compact \ tree_summarize \ refine

configLLM_TEMPERATURE

configLLM_MAX_TOKENS

configLLM_REQUEST_TIMEOUT

configMCP_HOST

configMCP_PORT

configLOG_LEVEL

// full audit trail

The full breakdown of what we checked, the deductions that landed, the network hosts, the dependency advisories, and concrete fix guidance is available to verified publishers.

// improvement guidance — verified publishers only

We have 2 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.

// embed badge in your README

[![M8ven Score](https://m8ven.ai/badge/mcp/hassan-butt4356-mcp-rag-assistant-dwtw3q)](https://m8ven.ai/mcp/hassan-butt4356-mcp-rag-assistant-dwtw3q)

commit: 70dfa5b320c37720062a89f15f0b8084c8592ba9

code hash: 09264d632b5dd733f57cc62080d3de3c1f13504795755fbf9b7339eb8a23296a

verified: 6/22/2026, 12:08:02 PM

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