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URSA: Universal Research and Scientific Agent

URSA is a flexible agentic workflow for accelerating scientific tasks. It helps connect language models, research tools, code execution, planning, persistent agent state, retrieval-augmented generation (RAG), and Model Context Protocol (MCP) servers into reusable scientific workflows.

Use URSA when you want to:

  • chat with a research assistant in the terminal or dashboard,
  • ask an agent to plan a technical task,
  • ask an execution agent to write, edit, and run code in a workspace,
  • connect to OpenAI, Anthropic, Google GenAI, Ollama, or an OpenAI-compatible endpoint,
  • persist named agents and reuse them across sessions,
  • ingest documents into persistent RAG collections,
  • compose multiple agents into teams or symposium-style peer review environments.
  • expose URSA as an MCP server for another client or agent framework,

Execution and network access

Some URSA agents can write files, run shell commands, and use web or MCP tools. Use a dedicated workspace, review actions carefully, and read the Sandboxing and information-control guidance before running high-trust or data-sensitive workflows.

Quick install

We recommend installing with uv:

uv venv --python 3.12 .venv
source .venv/bin/activate
uv pip install ursa-ai

If you prefer pip:

python -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install ursa-ai

For the web dashboard, install the dashboard extra:

uv pip install "ursa-ai[dashboard]"
# or
python -m pip install "ursa-ai[dashboard]"

See the Installation section for platform-specific details.

Quick first run

Create a reusable configuration file, for example config.yaml:

llm_model:
  model: openai:gpt-5.4
  api_key_env: OPENAI_API_KEY

Then run:

ursa --config config.yaml

Inside the URSA prompt, type help or try:

ursa> Summarize what URSA can help me do.
ursa> execute Write and run a Python script that prints the first 10 prime numbers.

Where to go next