Integrations
Your agents, your OS, your providers
25 coding agents and editors, four operating system targets, and a list of LLM and embedding providers that you can ignore, because everything works without one.
Many agents, one memory
Each agent connects to the same server. What Claude Code learned this morning is there when you open Codex this afternoon.
Agents and editors
Filter by status, then pick a row to get its install commands.
Claude Code Supported
# the memory tools, over MCP
ai-memory install-mcp --client claude-code --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent claude-code --apply
# or launch it managed; both wire themselves
ai-memory run claude
Hooks and MCP. Optional session-aware routing. Leave out --apply to print the change without writing it.
Codex Supported
# the memory tools, over MCP
ai-memory install-mcp --client codex --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent codex --apply
# or launch it managed; both wire themselves
ai-memory run codex
Hooks and MCP. Session end is wired from Codex CLI 0.145.0. Leave out --apply to print the change without writing it.
Cursor Supported
# the memory tools, over MCP
ai-memory install-mcp --client cursor --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent cursor --apply
MCP config and lifecycle hooks. Leave out --apply to print the change without writing it.
Gemini CLI Supported
# the memory tools, over MCP
ai-memory install-mcp --client gemini-cli --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent gemini-cli --apply
MCP config and lifecycle hooks. Leave out --apply to print the change without writing it.
OpenCode Supported
# the memory tools, over MCP
ai-memory install-mcp --client opencode --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent opencode --apply
# or launch it managed; both wire themselves
ai-memory run opencode
Remote MCP and a generated TypeScript plugin. Leave out --apply to print the change without writing it.
OpenCode 2 beta Supported
# the memory tools, over MCP
ai-memory install-mcp --client opencode2 --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent opencode2 --apply
# or launch it managed; both wire themselves
ai-memory run opencode2
Plugin for the beta API. Expect churn upstream. Leave out --apply to print the change without writing it.
Grok Build CLI Supported
# the memory tools, over MCP
ai-memory install-mcp --client grok --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent grok --apply
# or launch it managed; both wire themselves
ai-memory run grok
Capture works. Handoffs are picked up through MCP. Leave out --apply to print the change without writing it.
Devin CLI Supported
# the memory tools, over MCP
ai-memory install-mcp --client devin --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent devin --apply
Hooks and MCP, including post-compaction capture. Leave out --apply to print the change without writing it.
Kimi Code Supported
# the memory tools, over MCP
ai-memory install-mcp --client kimi-code --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent kimi-code --apply
# or launch it managed; both wire themselves
ai-memory run kimi
Ten hook events. Handoffs inject on the first prompt. Leave out --apply to print the change without writing it.
Kiro CLI Supported
# the memory tools, over MCP
ai-memory install-mcp --client kiro-cli --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent kiro-cli --apply
# or launch it managed; both wire themselves
ai-memory run kiro
Both the v2 and v3 engines. Leave out --apply to print the change without writing it.
Command Code Supported
# the memory tools, over MCP
ai-memory install-mcp --client command-code --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent command-code --apply
# or launch it managed; both wire themselves
ai-memory run command-code
MCP and four hook events, with native resume. Leave out --apply to print the change without writing it.
Antigravity CLI Supported
# the memory tools, over MCP
ai-memory install-mcp --client antigravity-cli --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent antigravity-cli --apply
# or launch it managed; both wire themselves
ai-memory run antigravity
Sessions close with finalize-session. Leave out --apply to print the change without writing it.
Pi Supported
# the memory tools, over MCP
ai-memory install-mcp --client pi --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent pi --apply
A generated extension gives capture and an MCP bridge. Leave out --apply to print the change without writing it.
Oh My Pi Supported
# the memory tools, over MCP
ai-memory install-mcp --client omp --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent omp --apply
Native MCP and a TypeScript extension. Leave out --apply to print the change without writing it.
OpenClaw Supported
# the memory tools, over MCP
ai-memory install-mcp --client openclaw --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent openclaw --apply
MCP config and native plugin hooks. Leave out --apply to print the change without writing it.
Zero Supported
# the memory tools, over MCP
ai-memory install-mcp --client zero --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent zero --apply
Capture includes subagent events. Leave out --apply to print the change without writing it.
ZCode Supported
# the memory tools, over MCP
ai-memory install-mcp --client zcode --apply
# automatic capture, through lifecycle hooks
ai-memory install-hooks --agent zcode --apply
Six triggers. Handoff injection works. Leave out --apply to print the change without writing it.
Crush Managed-only
# launch it through ai-memory
ai-memory run crush
Launch it with ai-memory run crush.
Pool Hooks-only
# stages the hook scripts and prints a snippet to paste into the agent’s settings
ai-memory install-hooks --agent pool --apply
Paste a generated hooks snippet into its settings.
Claude Desktop MCP-only
# the memory tools, over MCP
ai-memory install-mcp --client claude-desktop --apply
Connects through mcp-remote. Leave out --apply to print the change without writing it.
VS Code Copilot MCP-only
# the memory tools, over MCP
ai-memory install-mcp --client vscode-copilot --apply
Copilot exposes no lifecycle hooks yet. Leave out --apply to print the change without writing it.
Zed MCP-only
# the memory tools, over MCP
ai-memory install-mcp --client zed --apply
Registered as a context server. Leave out --apply to print the change without writing it.
Swival CLI MCP-only
# the memory tools, over MCP
ai-memory install-mcp --client swival --apply
Project-level MCP config. Leave out --apply to print the change without writing it.
Muse Code MCP-only
# the memory tools, over MCP
ai-memory install-mcp --client muse --apply
User-level MCP settings. Leave out --apply to print the change without writing it.
Hermes Agent Community
ai-memory ships no installer for this one. The server recognizes its hook events, and the plugin is maintained by the community. Review it before you install it: ai-memory-hermes-plugin on GitHub.
Community plugin by MrLuciano.
| Agent | Status | Notes | ai-memory run |
|---|---|---|---|
| Supported | Hooks and MCP. Optional session-aware routing. | Managed | |
| Supported | Hooks and MCP. Session end is wired from Codex CLI 0.145.0. | Managed | |
| Supported | MCP config and lifecycle hooks. | Direct launch | |
| Supported | MCP config and lifecycle hooks. | Direct launch | |
| Supported | Remote MCP and a generated TypeScript plugin. | Managed | |
| Supported | Plugin for the beta API. Expect churn upstream. | Managed | |
| Supported | Capture works. Handoffs are picked up through MCP. | Managed | |
| Supported | Hooks and MCP, including post-compaction capture. | Direct launch | |
| Supported | Ten hook events. Handoffs inject on the first prompt. | Managed | |
| Supported | Both the v2 and v3 engines. | Managed | |
| Supported | MCP and four hook events, with native resume. | Managed | |
| Supported | Sessions close with finalize-session. | Managed | |
| Supported | A generated extension gives capture and an MCP bridge. | Managed | |
| Supported | Native MCP and a TypeScript extension. | Managed | |
| Supported | MCP config and native plugin hooks. | Direct launch | |
| Supported | Capture includes subagent events. | Direct launch | |
| Supported | Six triggers. Handoff injection works. | Direct launch | |
| Managed-only | Launch it with ai-memory run crush. | Managed | |
| Hooks-only | Paste a generated hooks snippet into its settings. | Direct launch | |
| MCP-only | Connects through mcp-remote. | Direct launch | |
| MCP-only | Copilot exposes no lifecycle hooks yet. | Direct launch | |
| MCP-only | Registered as a context server. | Direct launch | |
| MCP-only | Project-level MCP config. | Direct launch | |
| MCP-only | User-level MCP settings. | Direct launch | |
| Community | Community plugin by MrLuciano. | Direct launch |
What each status means
- Supported
- Automatic capture through lifecycle hooks, plus the memory tools over MCP.
- MCP-only
- The agent can search and write memory. It exposes no lifecycle hooks, so nothing is captured automatically.
- Hooks-only
- Sessions are captured automatically. The agent has no MCP client to query memory with.
- Managed-only
- Works when launched through
ai-memory run. There is no separate hook installer. - Community
- A plugin maintained by the community, not installed by ai-memory itself.
- Experimental
- It ships and it works, with rough edges you should expect.
Per-agent details, config file locations and known quirks are in the support matrix and the MCP install guide.
Hooks capture, MCP answers
These are two separate connections, and a fully supported agent has both. The status labels above say which ones your agent gets.
Hooks
The agent’s lifecycle events fire a small command that records prompts, tool calls and session boundaries. You do nothing, and the agent spends no tokens on it. Secrets are stripped before anything is stored.
MCP
The agent gets memory tools it can call when the conversation needs them: search, read a page, write a page, accept a handoff. MCP-only agents can use memory fully, but nothing is captured unless they write it.
Operating systems
One Rust binary per platform. On Windows, WSL2 is the supported path and the native build is experimental.
| Platform | Status | How it installs | Notes |
|---|---|---|---|
| Linux | Supported | Release tarball, Docker or Podman image, or an AUR package | x86_64 and ARM64. Native binary, Docker or Podman, AUR packages with systemd units. |
| macOS | Supported | Release tarball with a launchd agent, Docker, or the menu bar app built from source | Apple Silicon and Intel. Native binary with a launchd agent, Docker, or a menu bar app you build from source. |
| Windows via WSL2 | Supported | The Linux binary, inside WSL2 | Follow the Linux path inside WSL2 and launch your agent from there. |
| Native Windows | Experimental | Release zip, Docker Desktop wrapper, or a source build | Release zip with ai-memory.exe, the Docker Desktop wrapper, or a source build. |
LLM and embedding providers
Both are optional. With neither, hooks still capture, search still works, and every session still ends with a summary page and a handoff.
Embeddings: local by default
Since 2.0, vector search runs in-process with a small open model. It needs no API key and no GPU. The model is about 87 MB, downloads in the background on first start, and hybrid search turns on at the next restart. If the download fails, search keeps working on full text.
- Local, in-process (the default)
- OpenAI
- Voyage
- Google Gemini
- GitHub Copilot
- Ollama, LM Studio, vLLM
Opt out with embedding_provider = "none". A provider you configured yourself is never overridden.
LLM: off by default
Add one when you want LLM-written consolidation, ai-memory bootstrap, richer linting, auto-improve or reranking. A small, fast model is the right size for this work, where the provider lets you pick one. With a Codex or ChatGPT login, keep the provider’s default model, because that backend rejects other model names. Subscription logins work, so a paid platform API key is not required.
- Anthropic
- OpenAI
- OpenAI OAuth / Codex CLI login
- GitHub Copilot
- Google Gemini
- OpenCode Go and Zen
- Ollama
- LM Studio
- vLLM
- Any OpenAI-compatible endpoint
Check a provider with ai-memory llm-test. Fallback chains are supported.
Models, defaults and costs are in the LLM providers guide and the local embeddings guide.
Your agent is not listed?
Anything that speaks MCP can use the memory tools today.
Register a remote HTTP MCP server at this address in your agent’s settings. Search, page reads and writes, and handoffs all work. Automatic capture needs lifecycle hooks, so without them the agent only remembers what it writes.
Want full support for it? The managed-harness contribution guide describes what an adapter has to prove, and the contribute page says where issues and pull requests go.
# the default local server
http://127.0.0.1:49374/mcp
Questions and answers
Which coding agents does ai-memory work with?
25 agents and editors are listed, including Claude Code, Codex, Cursor, Gemini CLI, OpenCode. 17 of them have both automatic capture through lifecycle hooks and the memory tools over MCP.
What is the difference between hooks and MCP?
Hooks capture sessions automatically: prompts, tool calls and session boundaries are recorded without the agent doing anything. MCP gives the agent tools it can call to search and write memory. A fully supported agent has both.
My agent is not listed. Can I still use it?
Yes, if it speaks MCP. Point it at http://127.0.0.1:49374/mcp and it can search and write memory. Without lifecycle hooks, nothing is captured automatically.
Do I need an LLM or an embedding provider?
No. Both are optional. Since 2.0 the default embeddings run in-process with a model of about 87 MB that downloads on first start, and no API key is involved.
Does ai-memory run on Windows?
Yes. WSL2 is supported through the Linux path. Native Windows is experimental and ships as a release zip with ai-memory.exe.
Give your agents a memory today.
Free and open source under the MIT license. You need no account and no API key.