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shinpr/mcp-local-rag

v0.16.1 Security

This release includes 1 security fix for security teams reviewing exposed deployments.

Published 16d MCP Search & Web
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →
This release patches 1 known CVE

Topics

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

Affected surfaces

deps

Summary

AI summary

Fixes incorrect handling of POSIX path backslashes and prevents false reporting of unrelated raw-data directories.

Changes in this release

Dependency High

Update dependencies to address security advisories.

Update dependencies to address security advisories.

Source: llm_adapter@2026-07-15

Confidence: high

 —
Bugfix Medium

Fix scoped operations for POSIX paths containing backslashes.

Fix scoped operations for POSIX paths containing backslashes.

Source: llm_adapter@2026-07-15

Confidence: high

 —
Bugfix Medium

Prevent unrelated `raw-data` directories from being reported as managed sources.

Prevent unrelated `raw-data` directories from being reported as managed sources.

Source: llm_adapter@2026-07-15

Confidence: high

 —
Bugfix Medium

Improve CLI reliability when commands fail.

Improve CLI reliability when commands fail.

Source: llm_adapter@2026-07-15

Confidence: high

 —
Bugfix Medium

Report the correct package version to MCP clients.

Report the correct package version to MCP clients.

Source: llm_adapter@2026-07-15

Confidence: high

 —
Full changelog
  • Fix scoped operations for POSIX paths containing backslashes.
  • Prevent unrelated raw-data directories from being reported as managed sources.
  • Improve CLI reliability when commands fail.
  • Report the correct package version to MCP clients.
  • Update dependencies to address security advisories.

Security Fixes

  • Update dependencies to address security advisories
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]