| FMRS | 51 / 100 · D | 75 / 100 · B |
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| Reliability | 8 / 20 | 12 / 20 |
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| Security and permissions | 10 / 20 | 16 / 20 |
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| Maintenance | 11 / 20 | 14 / 20 |
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| Documentation | 12 / 20 | 18 / 20 |
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| Setup experience | 10 / 20 | 15 / 20 |
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| Best for | - People who want a team of specialist agents coordinated by a Commander rather than a single chatbot
- Users who insist their data, keys, and agents stay on their own disk instead of a vendor cloud
- Users who want to mix multiple model providers or local model endpoints
- Users who want agents with private skills and memory that improve through reflection
| - Individuals or teams who prioritise privacy and offline operation and do not want data leaving the machine
- Users who share memory across multiple MCP clients such as Claude Code, Claude Desktop, Hermes Agent, OpenClaw, Cursor, Codex and Gemini CLI
- Scenarios that need encrypted storage, a hash-chained audit log and verifiable vault migration
- Users who want low-latency recall, a bundled embedding model and no extra LLM calls inside the memory layer
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| Not for | - People who just want a single all-purpose chatbot
- Users who want a fully hosted/cloud multi-agent team and don't mind their data living on a vendor's servers
- Developers who want a pure code library to embed in their own app (e.g. LangChain or CrewAI-style frameworks)
- Users who cannot run Node 20+ or are on musl-based distributions such as Alpine
| - Users who need cloud multi-device sync or a hosted team memory service; moving between machines means locking the vault and copying the file
- Users who expect the server itself to run an LLM that extracts facts and decides what to remember; Compartment explicitly keeps no LLM inside and leaves that to the host model
- Users who cannot keep a passphrase safe or who need a recovery path if it is lost, since Compartment never generates a password, seed or recovery phrase
- Deployments that require network transports such as SSE or streamable-http; this server is stdio only and opens no ports
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| Required permissions | - Read and write a local workspace directory (~/.orkas/ on macOS/Linux, <smallest non-system drive>:\.orkas\ on Windows)
- Store conversations, files, knowledge bases, custom agents, and API keys on your local disk
- Outbound network access to the model provider endpoints you configure (and to cloud embedding providers if you choose them)
- Run external CLI coding agents (Claude Code, Codex, OpenCode, Cline) as local subprocesses
- Download and verify local resources on first launch (embedding model ~95 MB, whisper.cpp runtime and multilingual speech model, FFmpeg, OfficeCLI, and others)
| - Read and write the vault file under the user's home directory, by default ~/.compartment/memory.vault, and its sibling settings file
- Access the session directory holding the unlock credential (configurable with COMPARTMENT_SESSION_DIR), which also carries the shared embedding process's Unix socket
- Optionally use the macOS keychain (compartment unlock --keychain is an explicit opt-in, and it survives reboots)
- Write or merge an mcpServers entry into each MCP client's own configuration file, taking a byte-exact backup first
- Install a PostToolUse hook for Claude Code that captures memory files the agent writes
- Serve a read-only dashboard on 127.0.0.1 behind a one-time random URL token
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| Risks and side effects | - API keys are stored on your machine's disk and can be read by any process or person with access to that account or device, so OS account security and disk encryption matter
- The Commander can drive external CLI coding agents and run them as local subprocesses, so a model may take actions with side effects; scope the working directory and permissions yourself
- Building from source installs a large dependency tree and prepares native runtimes, making first launch long and network-dependent
- On Linux, only glibc 2.34+ x64/arm64 is supported; Alpine and other musl-based distributions are not
- The packaged desktop app asks you to sign in on first launch; avoiding any account layer means using the source build in this repository
- The optional built-in Orkas model is billed by Orkas in credits, so paths other than your own keys incur additional cost
| - A leaked passphrase means the encrypted content can be decrypted; Compartment generates no recovery phrase and cannot recover a lost passphrase
- Enabling the memory_unlock tool places the passphrase in the model's context, which is why it is off by default
- If a 2FA keyfile is lost, for example a USB stick, the vault cannot be opened even with the passphrase
- `export --plaintext` writes the vault as unencrypted JSONL, so that file must be handled carefully
- Memory content can come from untrusted sources; recall wraps memories with a notice that they are stored data and content can be marked quarantined, but the host agent must still treat memory as data to limit prompt-injection risk
- The capture hook and client integration write into the user's own settings files, although the implementation backs up and merges rather than replacing
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| Supported clients | | Claude Desktop, Claude Code, Hermes Agent, OpenClaw, Cursor, VS Code, Codex, Gemini CLI, Cline, Roo Code, Zed, OpenCode, LM Studio, AnythingLLM, BoltAI, Goose, Kiro |
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| Tools | 6 | 14 |
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