GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
memfree
Good fit when
- When you need a hybrid approach combining traditional indexing with vector-based searches for more efficient AI-powered querying.
- If your project requires automated page generation alongside search functionality, making content creation and retrieval seamless.
Avoid when
- When your requirements strictly demand pure vector database solutions without the aid of traditional indexing methods.
- If you do not need an integrated page generator as part of your AI search capabilities.
- Pricing:
- freemium - Open-Source under MIT License, but commercial support might come with additional costs
- Requirements:
- Min 4 GB RAM; Requires Docker; Requires TypeScript for development or customization.; Best-suited for environments that can leverage serverless capabilities and React-based UI generation.
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Steady (62d since push)
- As of Sep 7, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 7, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
npm install memfreeSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A hybrid search solution integrating both traditional indexing methods and vector-based searches for efficient AI-powered querying. Also includes an automated page generation feature.
Capability facts
- Languages
- typescript
Source: github.language · Sep 7, 2026
Categories
Tags
README
One Click Deployment MemFree One Click Deployment guide License MemFree is backed by MemFree and licensed under MIT.
For agents
This page has a .md twin and JSON over the API.