mcp-local-rag vs cortex-memory

Common questions

What is the difference between mcp-local-rag and cortex-memory?

mcp-local-rag: Local-first RAG server for developers with semantic and keyword search capabilities.. cortex-memory: Persistent AI memory for Claude Code, Cursor & Cline with a VSCode extension and CLI.. See the comparison table for live GitHub stats and shared categories.

When should I choose mcp-local-rag over cortex-memory?

Choose mcp-local-rag over cortex-memory when Tags unique to mcp-local-rag: agent-skills, hybrid-search, local-first, privacy-first; mcp-local-rag ships an MCP server manifest; When you need to perform both semantic and keyword-based search operations within a local, privacy-focused environment tailored specifically for handling codebases and technical documentation.

When should I choose cortex-memory over mcp-local-rag?

Choose cortex-memory over mcp-local-rag when Pricing: Being open-source under the MIT license, cortex-memory is free for use, although specific pricing around value-added services or enterprise support are not detailed in the provided repository content.; Tags unique to cortex-memory: ai, ai-coding-assistant, ai-memory, claude-code; If you are working extensively with Claude Code, Cursor & Cline and want to automatically capture decisions, patterns, and context across sessions without configuration.

When should I avoid mcp-local-rag?

When you do not require a privacy-first approach and are willing to rely on cloud-based solutions that might offer more extensive feature sets beyond just keyword and semantic searches. If your use case involves scaling search capabilities across multiple remote databases or servers, as mcp-local-rag is best suited for local data only.

When should I avoid cortex-memory?

If you prefer not using tools that integrate deeply with specific AI platforms like Claude Code, which may limit its usefulness in environments where multiple or different platforms are used. In scenarios where custom configuration is required, as cortex-memory emphasizes zero-config setup which might not be adaptable to highly customized workflows.

Is mcp-local-rag or cortex-memory more popular on GitHub?

mcp-local-rag has more GitHub stars (370 vs 7). Stars measure visibility, not whether either tool fits your constraints.

Are mcp-local-rag and cortex-memory open source?

Yes - both are open-source projects on GitHub (mcp-local-rag: MIT, cortex-memory: MIT).

Where can I find alternatives to mcp-local-rag or cortex-memory?

GraphCanon lists graph-backed alternatives at mcp-local-rag alternatives and cortex-memory alternatives (mcp-local-rag markdown twin, cortex-memory markdown twin), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, mcp-local-rag or cortex-memory?

mcp-local-rag: Very active. cortex-memory: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for mcp-local-rag and cortex-memory?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: mcp-local-rag trust report; cortex-memory trust report.