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shinpr/mcp-local-rag

v0.14.1 Feature

This release adds 1 notable feature for engineering teams evaluating rollout.

Published 17d MCP Search & Web
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

agent-skills developer-tools hybrid-search local-first local-rag mcp
+6 more
mcp-server privacy-first llm semantic-search skills vector-db

Summary

AI summary

Visual ingest adds optional 'quality' profile for improved capture of in‑image text.

Changes in this release

Feature Medium

Visual ingest now offers two quality profiles (opt-in).

Visual ingest now offers two quality profiles (opt-in).

Source: granite4.1:8b-q6_K@2026-05-21

Confidence: low

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Feature Low

Visual ingest supports 'fast' and 'quality' quality profiles.

Visual ingest supports 'fast' and 'quality' quality profiles.

Source: granite4.1:30b@2026-05-21-audit

Confidence: low

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Feature Low

'fast' profile uses HuggingFaceTB/SmolVLM-256M-Instruct model by default.

'fast' profile uses HuggingFaceTB/SmolVLM-256M-Instruct model by default.

Source: granite4.1:30b@2026-05-21-audit

Confidence: low

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Feature Low

'quality' profile uses onnx-community/Qwen2.5-VL-3B-Instruct-ONNX for better text capture.

'quality' profile uses onnx-community/Qwen2.5-VL-3B-Instruct-ONNX for better text capture.

Source: granite4.1:30b@2026-05-21-audit

Confidence: low

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Full changelog

Changes

  • Visual ingest now offers two quality profiles (opt-in). When visual: true (MCP) or --visual (CLI) is set, a new visualQuality parameter (visualQuality: 'fast' | 'quality' on MCP ingest_file; --visual-quality fast|quality on CLI) selects the VLM. fast (default) keeps the v0.14.0 model HuggingFaceTB/SmolVLM-256M-Instruct. quality selects onnx-community/Qwen2.5-VL-3B-Instruct-ONNX for figures where in-image text (axis labels, panel sub-labels, flowchart nodes) needs to be captured reliably. Default behavior is unchanged; the quality profile is opt-in per ingest call.
View diff on GitHub

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About shinpr/mcp-local-rag

Privacy-first document search server running entirely locally. Supports semantic search over PDFs, DOCX, TXT, and Markdown files with LanceDB vector storage and local embeddings - no API keys or cloud services required.

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Related context

Beta — feedback welcome: [email protected]