Your AI Forgot Your
Project Again.
We Fixed That.
Eidos Memory gives any AI CLI persistent, compressed context. 95.6% fewer tokens. Works with Claude, Gemini, Qwen, and 9+ others.
Eidos Dashboard
Memory engine active
Token Savings
Context Chunks
+42 indexed today
Active Projects
3 synced via CRDT
Knowledge Graph
Recent Activity
Injected context
claude → auth module
Indexed
+42 chunks from ./src
Compressed
4,200 → 183 tokens
Retrieved
7 vectors for query
Synced
CRDT merge complete
Token Savings Benchmark
Real numbers from actual usage. Run eidos demo to see them yourself.
Problems We Solve
One install, zero config. Eidos Memory handles context for every AI tool on your machine.
Universal
Your AI tools each have their own memory — or none at all.
Eidos injects context into Claude, Gemini, Qwen, Aider, and 9+ other CLIs. One memory for every tool.
Local-first
Your code should never leave your machine.
Embeddings, AST parsing, and graph storage all run locally in ~/.eidos/. Zero cloud dependencies.
Privacy Firewall
Accidentally sending API keys or secrets to your AI?
.eidosignore excludes sensitive files. Automatic secret redaction for API keys, JWTs, and env vars.
Adaptive Token Budget
Not every question needs the whole codebase.
Eidos auto-detects whether you're debugging, implementing, or recalling — and adjusts context size accordingly.
Vector Search
Keyword search misses what matters. You need semantic understanding.
384-dim MiniLM or optional 768-dim BGE embeddings with sqlite-vec ANN for fast similarity search.
CRDT Sync
Your team's AI memory should sync — securely.
AES-256-GCM encrypted team sync via shared folder or self-hosted HTTP relay. CRDT-based conflict resolution.
Web Dashboard
See exactly what your AI knows — and what it's saving you.
vis-network graph explorer + savings charts at localhost:7842. Visualize your knowledge graph in real-time.
MCP Server
Your AI should be able to query its own memory.
Full MCP server with search, assemble, remember, and feedback tools for Claude Desktop, Cursor, and Continue.
Sub-10ms Latency
Context retrieval shouldn't slow you down.
Under 10ms latency. No noticeable delay in your AI coding workflow.
How It Works
Three steps. Zero config. Your AI gets persistent memory automatically.
Index
Eidos scans your codebase, chunks it into semantic units (functions, classes, modules), and creates vector embeddings. Everything stays local in ~/.eidos/.
Retrieve
When you ask a question, Eidos finds the most relevant chunks via vector search. Not the whole file — just the functions, decisions, and context that matter.
Compress
The retrieved context is compressed: function bodies become skeletons, conversation turns become micro-summaries, diffs become patch-only. 90-98% reduction.
Why EidosCore?
EidosCore replaces claude-mem, memory, graphify, and caveman with one tool.
| Feature | claude-mem | memory | graphify | EidosCore |
|---|---|---|---|---|
| Code-aware semantic search | ||||
| Conversation memory | ||||
| Automatic context injection | ||||
| Token-budgeted assembly | ||||
| Universal CLI adapters (9+) | ||||
| Session continuity (QMS) | ||||
| Self-learning retrieval | ||||
| Privacy-first (local-only) | ||||
| MCP server (14 tools) | ||||
| CRDT team sync |
Last updated May 2026. Based on publicly available feature lists.
Is Eidos Memory For You?
Eidos Memory is built for developers who:
Use Claude Code, Gemini CLI, Qwen, or Aider daily
Waste tokens re-explaining your project every session
Want their AI to remember debugging sessions from last week
Need context that follows them across different AI tools
Care about privacy — code never leaves their machine
Frequently Asked Questions
No. All embeddings, AST parsing, and graph storage run locally in ~/.eidos/. There are zero cloud dependencies. Your code never leaves your computer.
Claude Code, Gemini CLI, Qwen, Aider, llm, sgpt, mods, Open Interpreter, Continue, Cursor, Claude Desktop, and any OpenAI-compatible tool. One memory engine for all of them.
EidosCore replaces claude-mem, memory, graphify, and caveman with one tool. It adds automatic context injection, token-budgeted assembly, session continuity (QMS), and self-learning retrieval — none of which claude-mem offers.
Yes. MIT licensed. Local-first. No cloud dependency. No hidden costs, no API keys needed for the core functionality.
In our debugging benchmark: 1,245 words down to 57 words — a 95.6% reduction. At 50 prompts/day, that's roughly $90/month per developer in token costs saved.
No. Context retrieval completes in under 10ms. You won't notice any delay in your AI coding workflow.
What's Next
We're actively building. Here's what's coming.
Give Your AI a Memory
One install. Every AI CLI. Zero config. Your AI remembers everything.