Stop re-explaining yourself every time you switch tools, projects, or sessions.
Claude Code | Codex | Cursor | MCP compatible | 100% local
TL;DR: Engram is an MCP server that gives Claude Code, Codex, and Cursor a persistent identity layer — your profile, preferences, lessons learned, and key decisions stored as local JSON files. One write, every AI reads. 100% local, Apache 2.0.
AI coding tools are powerful, but they do not really know you.
Every time you switch from Claude Code to Codex, open Cursor, start a new session, or move into a different project, you often have to explain the same things again:
- how you prefer to communicate
- how the AI should approach code
- which project rules matter
- which mistakes should not happen again
- why earlier decisions were made
Engram stores that collaboration memory as local files, then exposes it through MCP so different AI tools can read the same user context.
The goal is simple: make every compatible AI tool start from the same understanding of you.
| Without Engram | With Engram |
|---|---|
| Every new session starts from zero | AI tools can load your identity and preferences |
| Switching tools loses accumulated context | Claude Code, Codex, and Cursor can read the same memory |
| Project rules live in scattered prompts | Rules and decisions are stored as local assets |
| Past mistakes get repeated | Lessons learned can follow you across tools |
| Memory is locked inside one product | Data stays local, editable, and portable |
Engram is not another chat app, agent framework, or hosted memory service. It is a small local memory layer that sits underneath the tools you already use.
Unlike session-memory tools that remember what happened in a task, Engram stores who you are — your identity, preferences, lessons, and decisions — so every AI tool starts from the same understanding of you as a person.
Engram fits anyone whose work involves accumulated judgment — not one-time tasks, but years of lessons, decisions, and hard-won standards that an AI tool should already know.
Developers
Your quality standards (test coverage, naming rules, which hacks you refuse to ship), architecture decisions, and hard-won lessons exist only in your head — and reset every session. With Engram, day one of a new project is not day one: your AI already knows your bottom line.
Investment analysts
Decisions get made but reasoning gets lost. Engram stores the full reasoning chain so six months later, "why did I pass on that?" has a real answer — and your analytical framework travels with you across every new analysis.
System architects
Architecture decisions need context: what you chose, what you ruled out, and why. Engram keeps living Architecture Decision Records that travel with you across companies and projects, queryable by any AI tool.
Backend developers
API quirks, integration gotchas, performance trade-offs — tacit knowledge that normally lives in your head and resets when you change jobs. Engram turns it into a searchable library that persists across everything.
Frontend and design
Design philosophy rarely gets documented in a way AI tools can use. Engram stores your real standards, UX lessons from real users, and the reasoning behind component decisions — so every project starts where your last one ended.
Vibe coders
You build with AI and move fast. The problem: every new session your AI starts from scratch — different style choices, inconsistent patterns, re-explaining the same preferences. Engram makes every tool consistent from session one: your stack, your patterns, your voice, already there.
All data lives under ~/.engram/ as plain JSON and Markdown files you can open, edit, back up, or migrate yourself.
- Identity: who you are, how you communicate, what languages you prefer
- Quality standards: your code review bar, test coverage expectations, what you refuse to ship
- Preferences: coding style, AI behavior, how you like explanations
- Trust boundaries: which fields to keep private, what tools can access
- Project snapshots: context for ongoing work, captured and reloadable
- Lessons learned: mistakes, surprises, things that worked and didn't
- Key decisions: what you chose, what you ruled out, and why
- Domain knowledge: reusable insights across projects and tools
Most memory tools are passive — you put things in, they give them back. Engram is also active.
Knowledge inheritance across projects
Describe a new project in plain text. get_knowledge_inheritance returns a curated starter pack of the most relevant lessons and decisions from everything you have ever worked on. Your tenth project benefits from all nine before it — automatically.
Passive knowledge capture
Paste a session summary into extract_session_insights and Engram automatically extracts and stores the lessons and decisions. No manual note-taking. Knowledge accumulates even when you are not thinking about it.
Works with tools that do not support MCP
ChatGPT, Gemini, Kimi — get_identity_card exports a ready-to-paste Markdown identity card. Your context travels even to tools that cannot connect directly.
Knowledge health and discovery
get_knowledge_overview surfaces stale lessons (not reviewed in 90+ days), gives a health score, and flags gaps worth revisiting. find_similar_knowledge finds overlapping items to merge. link_knowledge connects related lessons and decisions into a navigable knowledge graph.
Run Engram on your own machine. Data stays in ~/.engram/, AI tools connect over stdio.
git clone https://github.com/Patdolitse/engram.git
cd engram
pip install piia-engram # Install from PyPI (recommended)
# Or install from source: pip install -e .
python demos/setup_engram.pyAdd to your AI tool's MCP config:
{
"mcpServers": {
"engram": {
"command": "python",
"args": ["/path/to/engram/src/engram_core/mcp_server.py"]
}
}
}Restart your MCP-compatible client. A new session will call get_user_context automatically.
Run Engram on your own server and connect from anywhere.
# Install with remote support
pip install piia-engram[remote]
# Generate an auth token
python -c "import secrets; print(secrets.token_urlsafe(32))"
# Save the output, e.g. "abc123..."
# Start in SSE mode
ENGRAM_AUTH_TOKEN=abc123... python -m engram_core.mcp_server --transport sse --host 0.0.0.0 --port 8767{
"mcpServers": {
"engram": {
"url": "http://your-server:8767/sse",
"headers": {
"Authorization": "Bearer abc123..."
}
}
}
}{
"mcpServers": {
"engram": {
"url": "http://your-server:8767/sse",
"headers": {
"Authorization": "Bearer abc123..."
}
}
}
}Security notes:
- Always use HTTPS in production, behind nginx or caddy with TLS.
- The auth token protects your identity data. Keep it secret.
- Default bind is
127.0.0.1for localhost only. Use0.0.0.0only behind a reverse proxy. - Data stays on your server and never touches third-party clouds.
Engram exposes read, write, project, backup, and compatibility tools through MCP.
Common tools include:
| Tool | Purpose |
|---|---|
get_user_context |
Load the complete user context at the start of a session |
get_identity_card |
Export a Markdown identity card for tools without MCP |
get_profile |
Read the user profile, optionally filtered with safe=true |
get_preferences |
Read communication and workflow preferences |
get_trust_boundaries |
Read data access boundaries |
get_quality_standards |
Read quality expectations |
get_lessons |
Read reusable lessons learned |
get_decisions |
Read key decisions and reasons |
get_relevant_knowledge |
Find knowledge relevant to a project |
get_knowledge_inheritance |
Build a cross-project knowledge starter pack from free text |
save_project_snapshot |
Save project context for later sessions |
add_lesson |
Add a lesson learned |
add_decision |
Add a key decision |
bulk_add_knowledge |
Add multiple lessons or decisions in one call |
ingest_notes |
Parse free-form notes into lessons and decisions |
extract_session_insights |
Extract lessons and decisions from session summaries |
export_engram |
Export a full backup |
import_engram |
Import a backup |
export_engram_to_openclaw |
Export OpenClaw-compatible files |
import_engram_from_openclaw |
Import OpenClaw-compatible files |
search_knowledge |
Search lessons and decisions by weighted multi-term relevance |
get_knowledge_overview |
Knowledge overview: digest, health report, and stale checks |
get_related_knowledge |
Follow links between lessons and decisions |
find_similar_knowledge |
Find similar lessons and decisions by content |
export_knowledge_report |
Export a readable Markdown knowledge report |
link_knowledge |
Create a bidirectional link between two knowledge items |
unlink_knowledge |
Remove a bidirectional knowledge link |
merge_knowledge |
Merge a duplicate knowledge item into the primary item |
update_knowledge |
Update a lesson or decision by ID |
archive_knowledge |
Archive a lesson or decision by ID |
get_audit_log |
Get recent audit log entries |
~/.engram/
|-- schema_version.json
|-- identity/
| |-- profile.json
| |-- preferences.json
| |-- quality_standards.json
| `-- trust_boundaries.json
|-- knowledge/
| |-- lessons.json
| |-- decisions.json
| `-- domains.json
|-- projects/
| `-- {project_id}.json
|-- exports/
`-- compat/
`-- openclaw/
| Tool | Integration | Status |
|---|---|---|
| Claude Code | MCP over stdio | Tested |
| Codex | MCP over stdio | Tested |
| Cursor | MCP over stdio | Expected to work |
| Claude Desktop | MCP over stdio | Expected to work |
| OpenClaw | SOUL.md / MEMORY.md / USER.md import and export | Tested |
| ChatGPT / Gemini / Kimi | Markdown identity card fallback | Usable |
| Feature | Engram | Claude Memory | Manual CLAUDE.md |
Mem0 |
|---|---|---|---|---|
| Cross-tool sharing | Yes | Claude only | Tool-specific | Yes |
| Local storage | Yes | Cloud | Local | Cloud / hosted |
| Directly editable data | JSON / Markdown | Not visible | Yes | API-based |
| MCP standard | Yes | Not applicable | Not applicable | Yes |
| Portable backup | Copy files or export JSON | Limited | Copy files | API export |
| Model-agnostic | Yes | Claude-focused | Depends on the tool | Yes |
| Price | Free and open source | Included in subscription | Free | Free / paid tiers |
Engram is a human-directed, AI-assisted open-source project.
| Contributor | Role |
|---|---|
| @Patdolitse | Creator, product direction, strategy, ownership |
| Claude Code | Architecture, task planning, code review assistance |
| Codex | Implementation, testing, documentation assistance |
What is Engram? Engram is a local-first MCP server that gives AI coding tools (Claude Code, Codex, Cursor) a persistent identity layer. It stores who you are, how you work, what you have learned, and the decisions you have made — as local JSON files on your machine.
How is Engram different from other AI memory tools? Most AI memory tools store what happened in a session (task context, code changes). Engram stores who you are as a person — your identity, preferences, lessons, and decisions. This identity layer persists across tools, sessions, and projects. Your data is local JSON files you own and can edit directly.
Which AI tools does Engram support? Engram works with any MCP-compatible AI tool: Claude Code, OpenAI Codex, Cursor, Claude Desktop, and others. For tools without MCP support (ChatGPT, Gemini, Kimi), you can export a Markdown identity card and paste it in manually.
How do I install Engram?
git clone https://github.com/Patdolitse/engram.git
pip install piia-engram
# Or from source: cd engram && pip install -e .
python demos/setup_engram.pyThen add the MCP config and restart your AI tool. The AI will call get_user_context automatically at the start of each session.
Does Engram send data to the cloud?
All data is stored in ~/.engram/ on your local machine. Engram itself never uploads data anywhere. The optional read_web_content tool makes outbound HTTP requests to a local Reader service (localhost:7890) which may in turn fetch external URLs — but only when explicitly invoked. Core identity and knowledge tools make no network requests.
How many MCP tools does Engram provide? Engram exposes 37 MCP tools covering identity management, lessons learned, key decisions, project snapshots, bulk input, note ingestion, session insight extraction, weighted knowledge search, similarity discovery, merging, digesting, reporting, linking, health checks, and audit logging.
Is Engram free? Yes. Engram is free and open source under the Apache 2.0 license.
Engram is functional and actively used, but some things it intentionally does not do yet:
| Area | Current State | Planned |
|---|---|---|
| File safety | Atomic JSON writes with a shared portalocker file lock | Broader stress testing |
| Access control | restricted_fields filters profile fields from get_user_context and get_profile(safe=true) |
Per-caller ACL blocked by MCP caller identity |
| Encryption | Optional field-level AES-256-GCM encryption via ENGRAM_SECRET env var. Install pip install piia-engram[secure]. |
Full-disk encryption for all files (v4.0) |
| Audit logging | Optional access audit log via ENGRAM_AUDIT=1 env var. Logs to ~/.engram/audit.log. |
Per-caller audit (blocked by MCP spec) |
| Caller identity | MCP protocol doesn't pass tool identity | Blocked by MCP spec |
| Concurrent writes | Protected by file lock + atomic replace for Engram JSON writes | Network-filesystem edge cases not guaranteed |
What this means in practice:
- Don't store passwords, API keys, or client PII in Engram
- Any process with read access to
~/.engram/can read your data restricted_fieldsreduces what Engram emits in cold-start context, but it is not encryption or a true ACL
This is not a warning to avoid Engram — it's an honest description of what it is: a local memory layer for personal AI context. For personal use, it works well today.
Encrypt sensitive profile fields (email, phone, location, etc.) at rest:
pip install piia-engram[secure]
export ENGRAM_SECRET="your-strong-passphrase"Encrypted fields are stored as enc:v1:... in JSON files. Without ENGRAM_SECRET, Engram works normally with plaintext (backward compatible).
Track all read/write operations:
export ENGRAM_AUDIT=1Logs are written to ~/.engram/audit.log in JSON-lines format. Query with get_audit_log tool or grep.
Contributions, issues, and feedback are welcome.
See CONTRIBUTING.md. Chinese readers can also use CONTRIBUTING.zh-CN.md.
Apache 2.0. Engram is free software. Your memory belongs to you.