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memory and code intelligence for AI coding agents","maintainers":[{"name":"nano-step001","email":"kokoro.lehoang@gmail.com"},{"name":"nhonh","email":"hoainho.work@gmail.com"}],"readme":"# nano-brain\n\n**Built for agents. Not humans.**\n\nAgent-oriented memory and code intelligence over MCP. AI agents don't read docs — they call tools. nano-brain gives them structured context, symbol lookup, call-chain tracing, and change-impact analysis across sessions and repos.\n\n[![Go 1.23](https://img.shields.io/badge/Go-1.23-00ADD8?logo=go)](https://go.dev/)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)\n[![GitHub](https://img.shields.io/badge/GitHub-nano--step%2Fnano--brain-181717?logo=github)](https://github.com/nano-step/nano-brain)\n[![npm](https://img.shields.io/badge/npm-@nano--step%2Fnano--brain-CC3533?logo=npm)](https://www.npmjs.com/package/@nano-step/nano-brain)\n[![npm downloads](https://img.shields.io/npm/dw/@nano-step/nano-brain?logo=npm&label=downloads)](https://www.npmjs.com/package/@nano-step/nano-brain)\n[![Docker](https://img.shields.io/badge/Docker-2496ED?logo=docker&logoColor=white)](https://hub.docker.com/r/nano-step/nano-brain)\n[![Discord](https://img.shields.io/badge/Discord-5865F2?logo=discord&logoColor=white)](https://discord.gg/nano-brain)\n\n---\n\n## What it is\n\nnano-brain is an infrastructure layer between your AI agent and your code. It solves two problems agents have:\n\n1. **Session amnesia** — agents forget everything when a session ends. nano-brain harvests, indexes, and retrieves past sessions and saved decisions.\n2. **Codebase blindness** — agents can't cheaply trace dependencies, measure blast radius, or map an execution path. nano-brain builds a code graph and exposes it as MCP tools.\n\nSelf-hosted (Go binary + PostgreSQL), works with any MCP client (Claude Code, OpenCode, Cursor, …), and returns structured results — not raw file bytes.\n\n---\n\n## Install\n\n```bash\n# Recommended — one-line installer (no Node.js needed): downloads the prebuilt\n# binary for your platform from GitHub Releases and verifies its SHA-256.\ncurl -fsSL https://raw.githubusercontent.com/nano-step/nano-brain/master/install.sh | bash\n\n# Or via npm (handy if you're already in a JS/agent toolchain)\nnpm install -g @nano-step/nano-brain\n\n# Or build from source\nCGO_ENABLED=0 go build -o nano-brain ./cmd/nano-brain\n```\n\nPrefer to read the installer first? `curl -fsSL -o install.sh https://raw.githubusercontent.com/nano-step/nano-brain/master/install.sh && less install.sh && bash install.sh`.\n\n## Start\n\n```bash\n# One command — the interactive wizard provisions PostgreSQL (Docker or remote URL),\n# configures embeddings, starts the server, registers this project, and wires up your MCP client.\nnano-brain init\n```\n\nManual, per-step setup (VPS / team / no Docker / Windows): [docs/SETUP_AGENT.md](docs/SETUP_AGENT.md).\n\n### Connect your agent\n\nAdd to your MCP client config:\n\n```json\n{\n  \"mcp\": {\n    \"nano-brain\": { \"type\": \"remote\", \"url\": \"http://localhost:3100/mcp\" }\n  }\n}\n```\n\nBind a default workspace by appending `?workspace=<name-or-hash>` to the URL (e.g. `…/mcp?workspace=my-project`) so tool calls can omit the `workspace` argument. An explicit `workspace` argument always overrides it; the value must be a name or full hash (not `\"all\"`). Run `nano-brain workspaces list` to see registered names/hashes.\n\nFor OpenCode, you can bootstrap the current workspace with `npx @nano-step/nano-brain init -- opencode`. It installs a `/nano-brain` slash command that keeps the workspace config local at `.nanobrain/config.yml`.\n\n---\n\n## The agent workflow\n\nA cold agent should follow this order — it maps 1:1 to the tools:\n\n1. **Orient** — `memory_wake_up` for a workspace briefing (recent activity, collections, stats).\n2. **Locate the workspace** — `memory_workspaces_resolve(path)` returns a deterministic hash and whether it's registered. Registering the repo root also covers its subdirectories, so resolve the root, not a single sub-repo.\n3. **Understand** — `memory_query` (hybrid, best for natural-language questions), `memory_search` (exact identifiers/errors), or `memory_vsearch` (fuzzy concepts). Search returns 500-char snippets; fetch full text with `memory_get` only for the hits you keep.\n4. **Navigate code** — `memory_symbols` to find a definition (no indexing needed), then `memory_graph` / `memory_trace` for call chains and `memory_flow` for an HTTP route's execution.\n5. **Before a risky edit** — `memory_impact(node, direction=\"in\")` for the blast radius (who calls / imports this).\n6. **Persist** — `memory_write` to save a decision, lesson, or handoff for the next session.\n\n```\nwake_up → resolve ─▶ query / search / symbols ─▶ graph / trace / flow / impact ─▶ (edit) ─▶ write\n```\n\n---\n\n## MCP tools (18)\n\n**Search & recall**\n\n| Tool | Use it for |\n|------|------------|\n| `memory_query` | Hybrid BM25 + vector + RRF + recency — default first tool for broad questions |\n| `memory_search` | Exact keyword/BM25 — error strings, identifiers, config keys, channel/topic names |\n| `memory_vsearch` | Vector similarity — fuzzy concepts (best on single-concept queries) |\n| `memory_get` | Fetch full content (or a line range) for one known document/symbol |\n| `memory_write` | Persist a decision/lesson/handoff (supports `supersedes`) |\n| `memory_ticket` | All sessions tagged with a ticket ID (e.g. `PROJ-1234`) across the workspace |\n| `memory_wake_up` | Session-start briefing: recent memories, active collections, stats |\n| `memory_tags` | List collections and document counts |\n\n**Code intelligence**\n\n| Tool | Use it for |\n|------|------------|\n| `memory_symbols` | Find a function/type/interface/const by name (reads the filesystem — no indexing required) |\n| `memory_graph` | One-hop neighbors: direct callers/callees, imports, containment |\n| `memory_trace` | Downstream call chain from an entry symbol |\n| `memory_impact` | Reverse blast radius before an edit: who calls/imports this |\n| `memory_flow` | HTTP route execution flow (middleware → handler → downstream), Mermaid/sequence/JSON |\n| `memory_flowchart` | Control-flow graph of a single function (branches, loops, returns) |\n\n**Workspace & ops**\n\n| Tool | Use it for |\n|------|------------|\n| `memory_workspaces_resolve` | Resolve a path to its workspace hash + registration status |\n| `memory_workspaces_list` | List registered workspaces with paths, hashes, document counts |\n| `memory_status` | Server / DB / embedding-queue health |\n| `memory_update` | Trigger a delta re-scan / re-embedding for a workspace |\n\n> Every tool is self-describing over MCP — your client lists each tool's name, parameters, and description on connect.\n\n---\n\n## Architecture\n\n```mermaid\ngraph LR\n    A[Your AI Agent] -->|MCP| B[nano-brain]\n    B --> C[PostgreSQL + pgvector]\n    B --> D[Session Harvesting]\n    B --> E[Code Intelligence]\n    B --> F[Hybrid Search]\n    D --> D1[OpenCode Sessions]\n    D --> D2[Claude Code Sessions]\n    E --> E1[Symbol Graph]\n    E --> E2[Flow Diagrams]\n    E --> E3[Impact Analysis]\n    F --> F1[BM25 Full-Text]\n    F --> F2[Vector Similarity]\n    F --> F3[RRF Fusion]\n```\n\n- **Hybrid search** — BM25 full-text + pgvector HNSW cosine similarity + Reciprocal Rank Fusion + recency decay.\n- **Code intelligence** — symbol extraction, cross-file call-chain tracing, reverse-dependency (impact) analysis, and Mermaid flow/flowchart generation. Multi-language, including Ruby/Rails route + control-flow support.\n- **Session harvesting** — auto-ingest from OpenCode and Claude Code sessions, map-reduce LLM summarization, incremental harvest with dedup.\n\nCollections: `code` (indexed source + docs), `sessions` (harvested agent sessions), `memory` (agent-written decisions/notes).\n\n---\n\n## Performance\n\nCode-intelligence lookups (`memory_symbols`, `memory_graph`, `memory_impact`, `memory_vsearch`, exact `memory_search`) return in tens of milliseconds — fast enough that agents can run impact analysis on **every** edit rather than skipping it.\n\n### Search quality vs. document-memory tools\n\n| Metric | nano-brain | LlamaIndex | Qdrant/Mem0 |\n|--------|------------|------------|-------------|\n| P@5 | **80%** | 55% | 27% |\n| MRR | **95%** | — | — |\n| Code intelligence (symbols / impact / flow) | ✅ | ❌ | ❌ |\n\nMeasured on 60 domain-specific queries across three workspaces (a Go daemon, a TypeScript service, and a Rails app). nano-brain is the only one of these with code intelligence — the others target conversation memory and document retrieval.\n\n### Agent-oriented capability benchmarks\n\nEach benchmark runs a deterministic agent workflow — natural-language question → optimized query → symbol lookup — mirroring how an agent actually explores a codebase.\n\n| Workspace | Overall | Multi-tool | Search-QA | Symbol-Lookup |\n|-----------|---------|------------|-----------|---------------|\n| Go daemon | **1.000** | 1.000 | 1.000 | 1.000 |\n| TypeScript service | **0.885** | 1.000 | 0.817 | 1.000 |\n| Rails app | **0.795** | 1.000 | 0.726 | 0.667 |\n\nRun them: see the per-suite READMEs under [`benchmarks/`](benchmarks/).\n\n---\n\n## Tech stack\n\nGo 1.23 (single static binary, `CGO_ENABLED=0`) · PostgreSQL 17 + pgvector 0.8.2 (HNSW) · Echo v4 · sqlc · goose · zerolog · koanf · fsnotify · Ollama (or any OpenAI-compatible embeddings provider).\n\n## Configuration\n\n`~/.nano-brain/config.yml`:\n\n```yaml\nserver:   { host: localhost, port: 3100 }\ndatabase: { url: postgres://nanobrain:nanobrain@localhost:5432/nanobrain_dev }\nembedding: { provider: ollama, url: http://localhost:11434, model: nomic-embed-text }\nsearch:   { rrf_k: 60, recency_weight: 0.3, limit: 20 }\n```\n\nFull options: [docs/CONFIGURATION.md](docs/CONFIGURATION.md).\n\n## REST API\n\nEverything is available over MCP; a REST surface exists for scripting and ops (writes go through MCP). `GET /api/openapi.json` serves the live OpenAPI 3.0 spec — import it into Postman/Swagger.\n\n```bash\n# Understand\ncurl -X POST http://localhost:3100/api/v1/query   -H 'Content-Type: application/json' \\\n  -d '{\"workspace\":\"<hash>\",\"query\":\"how does authentication work\"}'\n# Blast radius\ncurl -X POST http://localhost:3100/api/v1/graph/impact -H 'Content-Type: application/json' \\\n  -d '{\"workspace\":\"<hash>\",\"node\":\"src/auth/login.ts\",\"direction\":\"in\"}'\n```\n\n---\n\n## Documentation\n\n- [Setup (agent / manual)](docs/SETUP_AGENT.md)\n- [Configuration](docs/CONFIGURATION.md)\n- [Architecture](docs/architecture.md)\n- [Features](docs/FEATURES.md)\n- [Roadmap](docs/ROADMAP.md)\n- [Changelog](CHANGELOG.md)\n\n## Contributing\n\nContributions welcome — open an issue or a PR.\n\n```bash\ngit clone https://github.com/nano-step/nano-brain.git && cd nano-brain\nCGO_ENABLED=0 go build -o nano-brain ./cmd/nano-brain\ngo test -race -short ./...                    # unit\ngo test -race -tags=integration ./...         # integration (needs PostgreSQL)\n```\n\nRegenerate the OpenAPI spec after route changes: `make generate-openapi`.\n\n## Community\n\n[GitHub Discussions](https://github.com/nano-step/nano-brain/discussions) · [Discord](https://discord.gg/nano-brain)\n\n## License\n\nLicensed under the MIT License.\n","readmeFilename":"README.md"}