Jenner SAS MCP Server

Run and validate SAS® programs from any Model Context Protocol client — Claude Desktop, Claude Code, Cursor, and others — without a SAS Institute licence. This server wraps the public Jenner run API (https://api.jenneranalytics.com), which executes SAS-compatible programs in a locked-down sandbox and returns the log, listing, output files, WORK datasets, and diagnostics as structured JSON.

Jenner is a SAS-compatible engine: write standard SAS (DATA steps, PROCs, macros) and it runs as-is.

What the model can do

Quickstart

The server speaks MCP over stdio. The fastest way to run it is with uv (no manual install step — uvx fetches and runs it on demand):

uvx jenner-sas-mcp

Or install it into an environment with pip:

pip install jenner-sas-mcp
jenner-sas-mcp        # starts the stdio server

Until the package is published to PyPI, install from this repository: uvx --from git+https://github.com/JennerAnalytics/jenner-sas-mcp jenner-sas-mcp or pip install git+https://github.com/JennerAnalytics/jenner-sas-mcp.

Configuration

All configuration is via environment variables:

Connect a client

Claude Desktop

Edit your claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json, Windows: %APPDATA%\Claude\claude_desktop_config.json) and add:

{
  "mcpServers": {
    "jenner-sas": {
      "command": "uvx",
      "args": ["jenner-sas-mcp"],
      "env": {
        "JENNER_API_KEY": "your-api-key-optional"
      }
    }
  }
}

Restart Claude Desktop. The jenner-sas tools appear in the tools menu. (A copy of this config lives in examples/claude_desktop_config.json.)

Claude Code

claude mcp add jenner-sas --env JENNER_API_KEY=your-key -- uvx jenner-sas-mcp

Or, for a project-scoped server checked into the repo, add it to .mcp.json:

{
  "mcpServers": {
    "jenner-sas": { "command": "uvx", "args": ["jenner-sas-mcp"] }
  }
}

Any other MCP client

Launch uvx jenner-sas-mcp (or jenner-sas-mcp) as a stdio server. Pass the environment variables above through your client's server configuration.

Try it

Once connected, ask the model things like:

• "Run this SAS program and show me the means: `proc means data=sashelp.class; var height weight; run;`"
• "Validate this program before we run it, then fix any errors."
• "Simulate 1000 draws from a normal, summarize them, and don't make it deterministic."
• "Run my regression and preview the `outstat` dataset."

A minimal first call the model makes under the hood:

run_sas(script="data a; x=1; output; run; proc print data=a; run;")
# -> { "ok": true, "exit_code": 0, "log": "...", "listing": "Obs  x\n 1   1",
#      "datasets": [{ "name": "a", "rows": 1, "columns": ["x"], ... }], ... }

How results come back

run_sas returns a compact, model-friendly summary of the run-result JSON:

• ok / exit_code — exit_code is the SAS severity (0 clean, 1 warnings

but still ok, ≥2 error); ok is the boolean exit_code < 2.

• log — the SAS log (the first place to read errors and NOTE:/WARNING:

lines). Clipped head+tail if very large; use get_run for the full text.

• listing — printed/stdout output (e.g. PROC PRINT, PROC MEANS tables).
• datasets — each WORK dataset's name, rows, columns, and a

preview_url/download_url.

• files — output artifacts (PNG/SVG/CSV/…) with a download url.
• diagnostics — parse and runtime warnings.
• run_id + access_token — pass these to get_run / dataset_preview to

retrieve full artifacts later.

Determinism is on by default: the RNG is seeded and today()/datetime() are frozen so the same program yields identical output. Set deterministic=false for genuine randomness.

Development

git clone https://github.com/JennerAnalytics/jenner-sas-mcp
cd jenner-sas-mcp
uv sync --extra dev          # or: pip install -e ".[dev]"
pytest                       # unit tests (no network)

Run the server against a local gateway:

JENNER_API_URL=http://127.0.0.1:3000 uv run jenner-sas-mcp

Inspect the tools interactively with the MCP Inspector:

npx @modelcontextprotocol/inspector uvx jenner-sas-mcp

License

Apache-2.0 — see LICENSE.

SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Jenner is not affiliated with or endorsed by SAS Institute Inc.