EvalForge Lite

EvalForge Lite

Compare text LLMs side by side. Write a few test prompts, pick up to four models across OpenRouter, Amazon Bedrock, Google Vertex AI and Microsoft Foundry, and EvalForge Lite sends the same prompts to all of them, scores the answers automatically, and shows a leaderboard with letter grades, response time, speed and estimated cost. Use it as a web app or as an MCP server for Claude and other assistants. You bring your own credentials, or the person hosting it keeps them on the server for you.

Documentation site: https://thejaredchapman.github.io/evalforge-lite/

Why use it

• Test on your own prompts. Choose models from evidence about your tasks, not a generic benchmark.
• Up to 4 models per run, across 4 backends. X (OpenRouter) and X@bedrock are separate targets, so you can check one model on two platforms in a single run.
• Automatic grading. A judge model scores each answer against your rubric, and rule checks (contains, regex, json_valid, max_length, available through the API and MCP) add a pass or fail. You get a 0-100 score and a letter grade.
• A second opinion on every response. Each answer is also evaluated on six criteria (answered, quality, instruction following, completeness, helpfulness, safety) with strengths and weaknesses written out.
• Speed and cost beside quality. Latency, tokens per second and estimated cost for every model, and a "What matters most?" selector that moves the "Best for ..." badge without a new run.
• Policy gate. Upload a company policy and prompts that violate it are blocked before any model is called. If the check itself fails, the prompt is blocked.
• Reports. Download a PDF or a CSV for any of your last five runs.
• No accounts, no database. Credentials are used for one request and not stored. Nothing is written to disk.

Quick start

1. Run the web app on your computer

Requires Python 3.10 or newer (3.12 recommended; download from https://www.python.org/downloads/) and git.

git clone https://github.com/thejaredchapman/evalforge-lite.git
cd evalforge-lite
python3.12 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python app.py

Open http://localhost:8000, paste a key for at least one backend (an OpenRouter API key is the quickest: https://openrouter.ai/workspaces/default/keys), add a test case, pick two to four models, and click Run comparison. Runs are limited to 3 per 8 hours per browser session. Full walkthrough: Getting started.

2. Use it from Claude (MCP server)

With uv installed:

uvx evalforge-lite

Add it to Claude Code in one line:

claude mcp add evalforge-lite -- uvx evalforge-lite

Or install the Claude Code plugin, which bundles the same server:

claude plugin marketplace add thejaredchapman/evalforge-lite
claude plugin install evalforge-lite@evalforge

Then ask your assistant to compare models. It gets 9 tools: list_models, suggest_models, list_availability, set_policy, evaluate_prompt, run_comparison, list_runs, get_report, get_report_csv. Details, Claude Desktop config and credential shapes: MCP server.

3. Host it for other people

Deploy with the included render.yaml (gunicorn, one worker) or any host that can run gunicorn --workers 1 --threads 4 --bind 0.0.0.0:$PORT app:app. By default every visitor supplies their own key. Optionally keep provider keys on the server with environment variables and a shared daily cap (50 per 24 hours by default). Keep it at one worker: all state is in memory per process. Full guide: Hosting and server-side keys.

Good to know

• The app does not read .env by itself. To use values from it, run set -a; source .env; set +a before python app.py.
• Each run is limited to 4 models, and each browser session gets 3 runs per 8 hours.
• All state lives in memory and is cleared when the server restarts. See Privacy and limits.
• Upgrading from an older version and reading the CSV or API fields? See the notes in Troubleshooting and FAQ.

Backends and credentials

Backend	What you provide
OpenRouter	One API key
Amazon Bedrock	A region, plus a Bedrock API key or AWS access keys (optional session token)
Google Vertex AI	A project id and region, plus an access token or service-account JSON
Microsoft Foundry	A resource name and region, plus an API key or Entra ID access token

A separate judge backend setting chooses where the judge and policy gate run. Bedrock, Vertex and Foundry costs are estimates from catalog prices, not your cloud bill. See Backends and credentials.

Documentation

Page	What is in it
Overview	What it is, who it is for, the three ways to use it
Getting started	Install, run, and your first comparison
Web app guide	Every part of the screen, in order
Comparing models	Reading metrics, grades, evaluation, cost and their limits
Backends and credentials	Keys, regions, X@backend targets
MCP server	Install paths, all 9 tools, example prompts
Hosting and server-side keys	Deploying for others, operator-held keys, daily cap
Troubleshooting and FAQ	Common messages, fixes, and notes on CSV/API field changes
Privacy and limits	What data goes where, what is stored, every limit

Test

pytest tests/ -v

Every model and HTTP call is mocked, so the suite needs no API key and makes no network calls.

Contributing

Contributions are welcome: bug reports, model-catalog updates, new checks, docs, and new backends. See CONTRIBUTING.md for setup, tests and the pull request process. When the app shows an error, the popup's Report an issue on GitHub button opens a pre-filled bug report.

License

MIT