OrangePro
About
Behavioral test gap analysis and grounded integration test generation via knowledge graph; finds untested behaviors, ranks by blast radius, proves via mutation kill.
Details
- Author
- Aamir Siddiqui
- GitHub stars
- 12
- Downloads
- 5,300
- Categories
- Developer Tools, Knowledge Base, Other
Jump to
- Grounding — the real files, symbols, and existing tests it cites
- Run hints — where to write it, how to run it
- Scenario bucket + technique — what failure mode it targets and how
- AI links appear as AI-linked suggestions
- AI flows are stored separately from deterministic flows
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
OrangeProCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
The README includes setup instructions such as npm install # or pnpm install / bun install / the repository's package manager.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"orangepro": {
"orangepro-mcp": {
"command": "npx",
"args": [
"-y",
"@orangepro/mcp-server@latest",
"start",
".",
"--prompt-version",
"v5"
]
}
}
}
}McpServers
{
"orangepro-mcp": {
"command": "npx",
"args": [
"-y",
"@orangepro/mcp-server@latest",
"start",
".",
"--prompt-version",
"v5"
]
}
}Find the behaviors your tests miss. Generate grounded tests that actually run.
OrangePro maps every public behavior in your codebase, scores each one by real test evidence, and shows you the structural blind spots before your users find them. Runs locally. Your code never leaves your machine.
npx -y @orangepro/mcp-server@latest start .
- What you get
- Evidence tiers
- Quick start
- Use with your coding agent
- How it works
- Language support
- Privacy
- CLI reference
- MCP tools
- Platform
- Contributing
One command produces an interactive HTML report:
npx -y @orangepro/mcp-server@latest start . open .orangepro/behavior-coverage.html
The report has two modes:Simple(integration-level blind spots, plain English) andExpert(full behavior list, evidence tiers, flows, system map). Toggle with the pill switch at the top.
→ Live example: Twenty CRM (5,237 behaviors mapped)
System map — entry lanes (GraphQL, HTTP, Jobs) flowing into services, sized by traffic, colored by evidence tier, red-ringed by risk.
Priority gaps of another open source Project HONO — top 20 unproven behaviors ranked by blast radius, with generated test drafts.
Every behavior gets exactly one tier. Nothing is labeled "tested" on faith.
"Dynamically Proven 0" is normal on first run.Proof requires running tests against targeted mutations. That's the trust model.
cd /path/to/your/repo npm install # install the repo's own dependencies first npx -y @orangepro/mcp-server@latest start . open .orangepro/behavior-coverage.html
No API key needed. The report shows your system map, evidence tiers, priority gaps, and delta since last run.
Want test generation?Add a model key (BYOK):
export ANTHROPIC_API_KEY="..." # or OPENAI_API_KEY / OLLAMA_BASE_URL npx -y @orangepro/mcp-server@latest start .
AI output never changes evidence tiers. Only the mutation-kill oracle can mint Dynamically Proven.
.orangepro/ ├── behavior-coverage.html ← open this ├── graph.json ← deterministic evidence graph ├── COVERAGE_REPORT.md ← coverage and gap summary └── ai/ ← candidate flows (when a key is configured) orangepro_generated/ ← generated tests; your source files are never touched
Each rerun shows adelta banner: what entered the codebase, what moved up in risk, what got resolved.
OrangePro runs as an MCP server. Add to your client's config:
{ "mcpServers": { "orangepro-local": { "command": "npx", "args": ["-y", "@orangepro/mcp-server@latest", "mcp"] } } }
"Useorangepro_start, thenorangepro_generate_testswith base_ref=main. Write each test to its suggested_path, run it, and report pass/fail."
The agent writes the test, runs it, callsorangepro_prove, and the behavior turns Dynamically Proven. One prompt, full loop.
Claude Code·Cursor·GitHub Copilot·Codex·Windsurf·OpenCode·VS Code
Any MCP-compatible agent can drive OrangePro. No vendor lock-in.
┌─────────────┐ ┌──────────────┐ ┌─────────────┐ │ Your Code │ ──► │ Knowledge │ ──► │ Evidence │ │ (any lang) │ │ Graph │ │ Tiers │ └─────────────┘ └──────────────┘ └─────────────┘ │ ┌──────┴──────┐ ▼ ▼ ┌───────────┐ ┌──────────┐ │ Gap Report│ │ Generate │ │ + Risks │ │ Tests │ └───────────┘ └──────────┘
Same code = same score. Deterministic. Always.
Static mapping works across many languages via tree-sitter. Dynamic proof is deliberately narrower — each language needs a runner, mutation locator, and sandbox profile.
- No stored source.Reads code in-process. Never uploads to an OrangePro server.
- No existing-source mutation.Never edits your source or test files.
- Your keys stay yours.Read from env at call time, never persisted.
- BYOK is direct.Code context goes to the model provider you configure. OrangePro is not in that path.
opro # analyze + report + agent next actions opro start --base main # same, scoped to a branch diff opro analyze # build the evidence graph opro score # graph readiness (0–100) opro gaps --limit 10 # top 10 untested behaviors opro generate --base main # tests for PR diff opro generate --single # top gap, whole repo opro prove # mutation-kill oracle opro rtm # traceability matrix opro export # metadata-only evidence pack opro mcp # run as MCP server (stdio) opro doctor # what evidence to add next opro coverage # ingest runtime coverage
Add--jsonto any read command for machine output. Runopro helpfor the full reference.
opro generate --base main # tests for what this branch changed opro generate --pr 1234 # checks out PR #1234 opro generate --changed # current branch diff vs main
- Grounding— the real files, symbols, and existing tests it cites
- Run hints— where to write it, how to run it
- Scenario bucket— what failure mode it targets
If dependencies aren't installed, tests are kept asManual tests(Given/When/Then steps with the blocker named). Install dependencies and re-run to convert them to runnable tests.
Generation is evidence-gated. A category is produced only when the graph has supporting evidence.
Analysis, scoring, and proof need no model key. Generation does.
Auto-detect order: OpenAI → Ollama → Anthropic. Override with--providerand--model.
Runopro setupto configure interactively. Keys stay in your environment — never written to graph, config, or artifacts.
With a provider key, OrangePro stages weak AI behavior→symbol links and AI-suggested candidate flows. These are review/generation worklists, not evidence:
- AI links appear asAI-linkedsuggestions.
- AI flows are stored separately from deterministic flows.
- Neither lane changes evidence tiers or denominator counts.
Use them when you want the agent to find likely service-boundary flows faster; ignore them for a deterministic-only report.
This repo is the free local tool. TheOrangePro platformadds:
- Persistent knowledge graph across PRs and repos
- PR/CI policy gates over evidence tiers and risk deltas
- Jira / Confluence / TestRail / OpenAPI enrichment
- Cross-repo intelligence and recurring-flow memory
- Production incident correlation and regression targeting
- Team dashboards and test lifecycle management
git clone https://github.com/OrangeproAI/orangepro-mcp.git cd orangepro-mcp && npm ci && npm run build npm test
PRs welcome. Please open an issue first for large changes.
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