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Head to head

Stop guessing which one. Put them side by side.

Up to 4 tools, same rows for each: what it is, what it really costs, the trap, and how to wire it up. The URL carries your picks — send it to anyone.

claude-memgraphify
Quick read
  • Editor's pick: claude-mem.
Fieldclaude-memgithub.comgraphifygithub.com
What it isCaptures what the agent does via hooks, compresses events into semantic summaries, stores them in SQLite with FTS5 plus a Chroma vector DB, and injects the relevant slice into future sessions. Progressive disclosure: search returns a ~50–100 token index before you fetch detail. ~91k stars.Turns a mixed corpus — code, docs, SQL schemas, configs, PDFs, images — into a queryable knowledge graph. Code extraction is deterministic and local; only prose and images route through Claude. Every edge is labeled EXTRACTED, INFERRED or AMBIGUOUS. Outputs graph.json, an interactive HTML visualization, a report and an Obsidian vault. ~107k stars.
CategoryMemory & contextMemory & context
Cost tierfreefree
PricingFree · Apache-2.0Free
Why builders pick itRuns with no intervention after install, which is why it beats a manual notes file. Content wrapped in <private> tags is excluded from storage.The mixed-corpus part is your project angle — it will ingest editorial PDFs, style guides and back-issue docs alongside the code, not just source files. The --wiki export produces agent-navigable markdown grouped by concept.
Watch out fornot loggednot logged
How to wire it upnpx claude-mem installuv tool install graphifyy
Editor's pickYesNo
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# Tool comparison — claude-mem vs graphify

Source: Kbaise, a directory of tools that work with Lovable projects.
Pick one and tell me why before writing any integration code.

## claude-mem (claude-mem)
- URL: https://github.com/thedotmack/claude-mem
- Category: Memory & context
- Cost: free — Free · Apache-2.0
- What it is: Captures what the agent does via hooks, compresses events into semantic summaries, stores them in SQLite with FTS5 plus a Chroma vector DB, and injects the relevant slice into future sessions. Progressive disclosure: search returns a ~50–100 token index before you fetch detail. ~91k stars.
- Why builders pick it: Runs with no intervention after install, which is why it beats a manual notes file. Content wrapped in <private> tags is excluded from storage.
- Wiring: npx claude-mem install
- Full dossier: /api/public/tools/claude-mem

## graphify (graphify)
- URL: https://github.com/Graphify-Labs/graphify
- Category: Memory & context
- Cost: free — Free
- What it is: Turns a mixed corpus — code, docs, SQL schemas, configs, PDFs, images — into a queryable knowledge graph. Code extraction is deterministic and local; only prose and images route through Claude. Every edge is labeled EXTRACTED, INFERRED or AMBIGUOUS. Outputs graph.json, an interactive HTML visualization, a report and an Obsidian vault. ~107k stars.
- Why builders pick it: The mixed-corpus part is your project angle — it will ingest editorial PDFs, style guides and back-issue docs alongside the code, not just source files. The --wiki export produces agent-navigable markdown grouped by concept.
- Wiring: uv tool install graphifyy
- Full dossier: /api/public/tools/graphify

## Quick read

- Editor's pick: claude-mem.

## Rules
1. Prefer the free tier when no budget was stated, and say what the ceiling is.
2. Read the full dossier before integrating.
3. Fetch /api/public/models before writing any AI model ID.

Agents can fetch the same thing: GET /api/public/compare?slugs=claude-mem,graphify