A local server that gives any AI coding tool a persistent memory, a map of your code, cheap delegate models, and guardrails it can't write past. Point your tool at it, or run it alongside. Your context follows you between tools.

Two parts:

• aimee-server is an assistant to one human. Learns how you work and what you expect. General purpose, but coding is what it does best, especially across large or multi-repo work.
• aimee-kb is a knowledge base for a whole corpus: a subject, a company, a team.

• Memory across sessions and tools. A curator distills each session into a typed knowledge base, dedupes facts, flags contradictions, and lets stale detail decay. Point a team at one kb and everyone works from the same memory. See KNOWLEDGE.md.
• Your code as a graph. aimee indexes your code into a symbol and call graph, spanning repos. The AI finds callers and traces an edit's blast radius before it writes. See CODE_INTELLIGENCE.md.
• Delegates that cut the bill. Route review, summarization, and boilerplate to the cheapest model that can do it. A local GPU model or a subscription plan costs nothing extra. The primary gets a compact result back. See DELEGATES.md.
• Guardrails. .env, keys, and prod configs are blocked before the AI touches them. Planning mode freezes writes. Every session is fully isolated by aimee. See SECURITY.md.
• Any model, any provider. Point a tool's OpenAI or Anthropic compatible API at aimee and it runs the turn on any model: Claude, GPT, Gemini, a model on your own GPU. Or run aimee beside the tool over MCP/ACP and it keeps its own model. Switch tools whenever.
• Workflows. Compose a job from typed steps and aimee runs it to a PR, with review panels and human sign-off gates where you want them. See WORKFLOWS.md.
• Run your own inference. Embeddings, reranking, and synthesis in one CPU or GPU container. The kb curates locally, no outside API calls. See KB_LLM_BACKENDS.md.
• A browser workspace. aimee-webchat: chat, a live code graph, a git project manager, an in-app VS Code editor, and dashboards. No terminal required. See DASHBOARD.md.

Core services are C. Hot paths run in single-digit milliseconds. Nothing phones home.

One container to start. The browser wizard brings up the rest.

git clone https://github.com/RakuenSoftware/aimee.git
cd aimee

# Start aimee-server. It mounts the host Docker socket so the wizard can launch
# aimee-kb, the LLM, and Postgres for you — CPU or GPU. No second compose command.
docker compose -f compose.server-managed.yaml up -d

Open https://localhost:8443, log in as aimee / aimee-local-dev, and run the setup wizard: pick a primary agent, choose CPU or GPU, connect a git host, pick workspaces. Its Deploy step brings up aimee-kb, the LLM, and Postgres. Change the login (AIMEE_WEBCHAT_USER / AIMEE_WEBCHAT_PASSWORD) before you put it on a network.

Then install the aimee CLI on each dev machine and point it at the server:

aimee remote set https://host:8743 <token>   # AIMEE_TLS_INSECURE=1 for the self-signed cert
aimee status                                  # server, DB1, and kb health

aimee wires its hooks and MCP server into your AI coding tools on first run — opt out with AIMEE_NO_CLIENT_INTEGRATIONS=1.

QUICKSTART.md walks the full setup. Every deployment topology and the from-source install live in Deployment and operations. Questions? Join the Discord.

aimee memory store myhost "PVE at 10.0.0.1"   # a fact the AI keeps across sessions
aimee memory search "proxmox"
aimee delegate review "Review this PR"         # route to a cheaper model
aimee status

More references live under docs/.

Questions and discussion on the aimee Discord: https://discord.gg/FjGjvcgAqz.

Copyright (C) 2026 The aimee authors. Licensed under the GNU AGPL v3.0 (AGPL-3.0). See LICENSE and NOTICE.

If the AGPL doesn't suit you, other terms can be discussed. Contact jbailes@gmail.com. Bundled third-party components (cJSON, the generated SDKs under api/sdks/) are licensed separately; see NOTICE.