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DimensionOrkasOpen-source, local-first multi-agent AI desktop client — command your AI agent team with chat.BioMCPOne binary. One grammar. Evidence from the biomedical sources you already trust.
FMRS51 / 100 · D75 / 100 · B
Reliability8 / 2010 / 20
Security and permissions10 / 2016 / 20
Maintenance11 / 2018 / 20
Documentation12 / 2017 / 20
Setup experience10 / 2014 / 20
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
  • Biomedical researchers
  • Clinicians
  • AI agents that need efficient access to biomedical literature and data analysis
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 needing to write to upstream databases (read-only)
  • Users requiring direct access to closed datasets (e.g., COSMIC is not directly integrated)
  • Users expecting all advanced features without API keys
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)
  • Requires internet access to query public biomedical APIs
  • Optional API keys (NCBI, Semantic Scholar, OpenFDA, etc.) to improve rate limits or unlock features
  • Local read/write access for skills, cache, and local study data (e.g., `~/.local/share/biomcp`)
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
  • Upstream API rate limits may affect performance
  • Some data sources (e.g., KEGG) have licensing terms that restrict non-academic use
  • Features requiring API keys (e.g., OncoKB) may be incomplete without them
  • Local binary installations need regular updates for compatibility
Supported clientsClaude Desktop, Claude Code, Codex, Other MCP stdio clients
Tools611