Portable memory layer for AI agents -*pre-release
git clone https://github.com/botzrDev/dreamd && cp dreamd/*.md ~/.claude/agents/Resumen de Subagents
# dreamd
[](./LICENSE)

[](#platforms)
[](#status)
**The plain files in your repo are the memory. dreamd is the local server that reads and writes them.**
Drop a `.agent/` folder in the project. Claude Code, Cursor, Cline, and other MCP-aware harnesses share it. What one agent learns, the next already knows. You can `cat`, `grep`, `git diff`, and hand-edit every byte.
This is not "another memory product." It is a storage-model wedge: the filesystem is the source of truth, and the MCP tools (`search_nodes` / `append_node`) are a thin interface over those files.
**Open core:** Apache-2.0 core today, self-hosted only. Premium features may ship later. Do not read this as free-forever for everything.
```bash
npx -y dreamd-mcp init # scaffold .agent/
npx -y dreamd-mcp # MCP server (stdio)
```
> First run prompts once. Press `y`, or keep using `npx -y dreamd-mcp`.
---
## The moment it earns its name
```text
~/project $ npx -y dreamd-mcp init
# Claude Code, Tuesday:
you > axum keeps blowing up when I unwrap in route handlers
claude> filed under rust::error_handling::axum_rejection
# Cursor, Friday, fresh session:
you > why is this build failing?
cursor> You're unwrapping in a route handler. dreamd has a
lesson from Tuesday: axum needs IntoResponse on
custom Error types. Try `?` and a typed error.
```
No re-explaining. No re-pasting. Same `.agent/` folder, every harness.
---
## Install
### npm (recommended)
```bash
npx -y dreamd-mcp init
npx -y dreamd-mcp
```
Requires a project root sentinel (`.git/`, `Cargo.toml`, `package.json`, or `pyproject.toml`).
### Cargo / from source
```bash
git clone https://github.com/botzrDev/dreamd.git
cd dreamd
cargo install --path crates/dreamd-cli
```
See [CONTRIBUTING.md](./CONTRIBUTING.md) for the full dev setup.
---
## Quick start (< 30 seconds)
If `~/your-project` is a brand-new folder, run `git init` first (or make sure it contains one of the supported root sentinels).
```bash
cd ~/your-project
npx -y dreamd-mcp init
# Terminal 1: shared daemon (recommended when several agents write)
dreamd watch
# Terminal 2: MCP server for your harness
npx -y dreamd-mcp
```
Ask the agent to search memory for something you just learned. It calls `search_nodes` and recalls prior context.
```bash
cat .agent/episodic/AGENT_LEARNINGS.jsonl
dreamd doctor
```
Adapters: [Claude Code](./adapters/claude-code/README.md) · [Cursor](./adapters/cursor/README.md)
---
## What dreamd writes
| Location | Contents | Commit? |
|---|---|---|
| `<project>/.agent/` | Episodic JSONL, semantic lessons, personal prefs | **Yes** (this is the shared memory) |
| `<project>/.agent/.dreamd/` | Local index, daemon state, config template | No (gitignored by `init`) |
| `~/.agent/registry.toml` | Which projects have a store | No |
| `~/.agent/dreamd.sock` | Daemon API socket (while running) | No |
`dreamd init` is idempotent. To uninstall from a machine — stop local servers, remove the socket, unregister the current project, clear caches — run `dreamd uninstall` (project `.agent/` stores are left in place). Advanced, registry-only: `dreamd init --uninstall-project` unregisters the current project and touches nothing else.
---
## Architecture (one paragraph)
Agents talk to dreamd over MCP (`search_nodes`, `append_node`). The MCP server proxies to a single-writer daemon (`dreamd watch`) over HTTP on a Unix domain socket, or runs in-process when no daemon is present. The coordinator appends to `AGENT_LEARNINGS.jsonl` and feeds a Tantivy BM25 index. Recall ranks hits with a query-time salience formula (BM25 × age decay × pain × importance × recurrence). Each hit carries `source_harness` and `skill_action`, so recall is attributable across harnesses. The dream cycle consolidates episodic learnings into `LESSONS.md` under WAL protection.
v0.1 recall is deliberately lexical (BM25 + salience). That is a scope choice, not a scoreboard claim. Semantic / embedding recall is out of scope until after v0.1.
Details: [ARCHITECTURE.md](./ARCHITECTURE.md) · [SPEC.md](./SPEC.md) · [docs/http-api.md](./docs/http-api.md)
---
## FAQ
**Is this the first / only cross-harness memory?** No. Other projects exist (including large ones). dreamd owns the storage-model wedge: plain files you already version-control, not a category claim.
**Do I need Rust?** No for the recommended path. `npx -y dreamd-mcp` downloads a prebuilt binary. Rust is only required if you build from source.
**Where does memory live?** In `<project>/.agent/`. The daemon and index under `.agent/.dreamd/` are local and gitignored. You can read and edit the JSONL / Markdown by hand; durable appends should go through the daemon / MCP so the writer stays single-writer.
**What if I want a full wipe?** See [Full fresh store](./docs/troubleshooting.md#how-do-i-reset-or-clear-memory). There is no `dreamd reset --all`. To uninstall dreamd itself, run `dreamd uninstall` — details: [packages/dreamd-mcp/README.md](./packages/dreamd-mcp/README.md#uninstall--reset).
**Windows?** Not in v0.1. Linux and macOS only. Windows lifecycle is planned for v0.1.1.
**Is everything free forever?** Apache-2.0 core is open. Premium may come later. Self-hosted only in v0.1 (no hosted SaaS).
More troubleshooting: [docs/troubleshooting.md](./docs/troubleshooting.md).
---
## Roadmap
| When | What |
|---|---|
| **v0.1** (~2026-08-09) | BM25 lexical recall, Linux + macOS, deterministic dream cycle, npm `dreamd-mcp` |
| **v0.1.1** | Windows lifecycle, semantic / embedding recall, LLM-assisted dream cycle (not claimed in v0.1) |
| **Oct 2026** | State-Drift benchmark publish (dreamd is one row; conflict of interest disclosed) |
v0.1.1 features are intentionally not implemented or documented as shipped in v0.1 code.
---
## Documentation
| Doc | What |
|---|---|
| [GUIDE.md](./GUIDE.md) | 20-minute tutorial walkthrough |
| [docs/README.md](./docs/README.md) | Full documentation index |
| [docs/http-api.md](./docs/http-api.md) | REST API over Unix socket |
| [docs/configuration.md](./docs/configuration.md) | TOML config and env vars |
| [docs/troubleshooting.md](./docs/troubleshooting.md) | Common failures |
| [docs/glossary.md](./docs/glossary.md) | Domain terms |
| [SPEC.md](./SPEC.md) | On-disk contract |
| [ARCHITECTURE.md](./ARCHITECTURE.md) | Engineering decisions |
| [CONTRIBUTING.md](./CONTRIBUTING.md) | Dev setup and RFC process |
| [SECURITY.md](./SECURITY.md) | Threat model |
| [docs/marketing.md](./docs/marketing.md) | Product story and positioning |
Warm recall latency numbers (local Criterion benches) live in [PERF.md](./PERF.md) if you want them. They are not the product pitch.
---
## Status
**v0.1 targeting 2026-08-09.** Daemon commands available today: `init`, `dream`, `doctor`, `mcp`, `watch`, `reset workspace`, `version`. npm package: `dreamd-mcp` (floating: `npx -y dreamd-mcp`). Linux and macOS.
| Layer | Status |
|---|---|
| `SPEC.md` v0.1 | Shipped |
| Reference implementation (daemon, HTTP API, dream cycle, Tantivy recall) | In progress |
| MCP server (`dreamd mcp` + `npx dreamd-mcp` shim) | Shipped on npm |
| CI / cross-platform matrix | Lint, test, build, binary-size gate, DCO |
| Conformance | Reference-impl alpha suites (`scripts/alpha/`); no formal certification in v0.1 |
---
## State-Drift benchmark (Oct 2026)
A separate, reproducible eval measuring whether memory systems correctly update superseded facts. dreamd is one row in the table, published regardless of placement. Conflict of interest is disclosed; configs use each maintainer's documented defaults; raw outputs are committed for audit. Methodology: [scripts/benchmark/README.md](./scripts/benchmark/README.md).
---
## Platforms
v0.1: Linux and macOS. Windows in v0.1.1.
---
## Contributing
See [CONTRIBUTING.md](./CONTRIBUTING.md). By participating you agree to the [Code of Conduct](./CODE_OF_CONDUCT.md). Security reports: [SECURITY.md](./SECURITY.md) (do not open a public issue for vulnerabilities).
## License
Apache-2.0. See [LICENSE](./LICENSE) and [NOTICE](./NOTICE).
Lo que la gente pregunta sobre dreamd
¿Qué es botzrDev/dreamd?
+
botzrDev/dreamd es subagents para el ecosistema de Claude AI. Portable memory layer for AI agents -*pre-release Tiene 4 estrellas en GitHub y se actualizó por última vez today.
¿Cómo se instala dreamd?
+
Puedes instalar dreamd clonando el repositorio (https://github.com/botzrDev/dreamd) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar botzrDev/dreamd?
+
botzrDev/dreamd aún no ha sido auditado por nuestro agente de seguridad. Revisa el repositorio original en GitHub antes de usarlo en producción.
¿Quién mantiene botzrDev/dreamd?
+
botzrDev/dreamd es mantenido por botzrDev. La última actividad registrada en GitHub es de today, con 6 issues abiertos.
¿Hay alternativas a dreamd?
+
Sí. En ClaudeWave puedes explorar subagents similares en /categories/agents, ordenados por popularidad o actividad reciente.
Despliega dreamd en tu cloud
Lleva este repo a producción en minutos. Cada plataforma genera su propio entorno con variables de entorno editables.
¿Mantienes este repo? Añade un badge a tu README
Pega el badge en tu README de GitHub para mostrar que está auditado por ClaudeWave. Cada badge enlaza de vuelta a esta página y muestra el Trust Score actual.
[](https://claudewave.com/repo/botzrdev-dreamd)<a href="https://claudewave.com/repo/botzrdev-dreamd"><img src="https://claudewave.com/api/badge/botzrdev-dreamd" alt="Featured on ClaudeWave: botzrDev/dreamd" width="320" height="64" /></a>Más Subagents
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
The agent that grows with you
Java 面试 & 后端通用面试指南,覆盖计算机基础、数据库、分布式、高并发、系统设计与 AI 应用开发
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.
The agent engineering platform.
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.