Biomni
Biomni: a general-purpose biomedical AI agent
Biomni is a general-purpose biomedical AI agent that autonomously executes diverse research tasks across multiple biomedical domains. Built by Stanford SNAP Lab, it combines large language model reasoning with retrieval-augmented planning and code execution to help scientists enhance productivity and generate testable hypotheses. The agent supports natural language task specification for activities like CRISPR screen planning, scRNA-seq annotation, and ADMET property prediction. It includes integration with external tools via Model Context Protocol (MCP), a web-based Gradio interface, and access to a curated Know-How Library of biomedical best practices.
Key Features
Use Cases
- 01Planning and designing CRISPR screens to identify genes regulating specific biological processes
- 02Performing single-cell RNA sequencing annotation and generating research hypotheses
- 03Predicting ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) properties for drug compounds
- 04Automating GWAS causal gene identification and variant prioritization
- 05Diagnosing rare diseases and identifying patient-specific genetic variants
- 06Retrieving and analyzing scientific literature for biomedical research questions
Related Agents
View morehermes-agent
The agent that grows with you
agency-agents
A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers. Each agent is a specialized expert with personality, processes, and proven deliverables.
openinterpreter
A coding agent for open models like Kimi K3
cline
Autonomous coding agent as an SDK, IDE extension, or CLI assistant.
Biomni — FAQ
What is Biomni?+
Biomni is a general-purpose AI agent designed specifically for biomedical research that autonomously executes tasks like CRISPR screen planning, genomic analysis, and drug property prediction using natural language commands. It combines LLM reasoning with code execution and retrieval-augmented planning across diverse biological subfields.
How do I install Biomni?+
First run the provided setup.sh script to create the conda environment, then activate it with 'conda activate biomni_e1', and install via 'pip install biomni --upgrade'. You must configure API keys for at least one LLM provider (Anthropic, OpenAI, Azure, Gemini, Groq, or AWS Bedrock) using either a .env file or environment variables.
What API keys are required to use Biomni?+
At minimum, you need an API key from one LLM provider: Anthropic (for Claude models), OpenAI, Azure OpenAI, Google Gemini, Groq, or AWS Bedrock. The ANTHROPIC_API_KEY is most commonly used, but you can configure any supported provider via the LLM_SOURCE environment variable.
Is Biomni free to use?+
Biomni itself is open-source under Apache 2.0 license, but you'll incur costs from your chosen LLM provider's API usage. Some integrated tools, databases, or components may have restrictive commercial licenses, so review each component before commercial deployment.
Which AI clients does Biomni work with?+
Biomni is a standalone agent system that doesn't require integration with clients like Claude Desktop or Cursor. It runs independently via Python API or through its built-in Gradio web interface at localhost:7860, and can also be accessed via the hosted web platform at biomni.stanford.edu.
Can I extend Biomni with custom tools?+
Yes, Biomni supports Model Context Protocol (MCP) for integrating external tools and custom servers. You can add MCP servers via agent.add_mcp(config_path='mcp_config.yaml') and contribute new tools, datasets, or know-how documents to the project via pull requests.
How do I install Biomni?+
Open the source repository on GitHub and follow its README. Biomni is a agent — MCP Agents Market links you directly to the official repo.
Is Biomni free?+
Biomni is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.