OrangePro MCP is a rigorously designed local testing tool: it strictly separates deterministic analysis from mutation-based proof, treats AI as an auxiliary lane that never pollutes evidence tiers, and ships 18 well-documented MCP tools with clear privacy guarantees. Dynamic proof currently covers only TypeScript/JavaScript, Python, Go, and Java; hosted platform features are out of scope for this repo. A solid choice for teams wanting auditable gap analysis and grounded test generation.
Strongest · Security and permissions 18/20 Weakest · Reliability 12/20
Static review · not runListed 2026-09-07
Read the FMRS scoring method →Runtime：Node.js
OPENAI_API_KEY
Optional OpenAI BYOK key for AI candidate links and test generation; get one from your OpenAI account.
ANTHROPIC_API_KEY
Optional Anthropic BYOK key for AI candidate links and test generation; get one from the Anthropic console.
OLLAMA_BASE_URL
Optional local Ollama endpoint (no key needed) for local AI generation; point it at your locally running Ollama service.
OPENAI_BASE_URL
Optional override for an OpenAI-compatible endpoint URL (custom or proxied providers).
OPENAI_MODEL
Optional override for the default OpenAI model name.
ANTHROPIC_MODEL
Optional override for the default Anthropic model name.
OLLAMA_MODEL
Optional override for the default Ollama model name.
1) Install the target repository's dependencies first (npm/pnpm/bun install). 2) Optional: export ANTHROPIC_API_KEY, OPENAI_API_KEY, or OLLAMA_BASE_URL to enable AI candidate links and test generation. 3) Run npx -y @orangepro/mcp-server@latest start . --prompt-version v5, then open .orangepro/behavior-coverage.html. 4) Run as an MCP server: npx -y @orangepro/mcp-server@latest mcp; or add {"mcpServers":{"orangepro-local":{"command":"npx","args":["-y","@orangepro/mcp-server@latest","mcp"]}}} to your client's MCP config. Alternatively use opro agent --client claude-code (or cursor/codex/opencode/generic) to print exact client config.
{"mcpServers":{"orangepro-local":{"command":"npx","args":["-y","@orangepro/mcp-server@latest","mcp"]}}}
Shown for Claude Code. Other clients may use a different file or key (VS Code uses "servers") — the configurator below converts it.
{
"servers": {
"orangepro-local": {
"command": "npx",
"args": [
"-y",
"@orangepro/mcp-server@latest",
"mcp"
]
}
}
}
Goes in your project's .vscode/mcp.json (VS Code uses a "servers" key).
claude mcp add orangepro-local -- npx -y @orangepro/mcp-server@latest mcp
Run it in a terminal; replace any <…> placeholders with your own values first.
Confirm the 18 orangepro_* tools (starting with orangepro_start) appear in your client's tool list, then ask it to run orangepro_start on the current repo; a report written to .orangepro/behavior-coverage.html proves the connection works.
Once connected, you can ask your AI assistant things like:
No matching tools
Listed from the project's documentation, not tested by this site.
OrangePro is a local-first CLI and MCP server (stdio transport) that builds a knowledge graph from your local checkout using tree-sitter, maps every behavior, and assigns each an evidence tier (Dynamically Proven, Runtime-covered, Statically Linked, Unconfirmed Candidate, No Signal). It ranks test gaps by blast radius, generates integration-level tests grounded in real symbols rather than hallucinated imports, and dynamically proves behaviors via a mutation-kill oracle. Analysis, scoring, and proof require no model key; AI candidate links and test generation use an optional BYOK key (OpenAI, Anthropic, or local Ollama). AI output never changes evidence tiers — only a mutation kill can mint Dynamically Proven. All code reading happens in-process; source is never uploaded and existing files are never mutated.
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Source revision 405209f3c533 Data synced 2026-10-19 Read the FMRS scoring method