{"data":{"kind":"file","path":"README.md","version_id":"fndy0syj4uyco12qn7ymq15t","entry":{"name":"README.md","path":"README.md","is_directory":false,"size":1585,"modified_at":"2026-02-06T11:15:14.912000","content_hash":"0942aba2d91bee48eebb9ad23e57b8e5a2ecb0ef19ba355e9e4bb518f3d1015c"},"entries":[],"content":"# mcp-search-env\n\n<a href=\"https://github.com/PrimeIntellect-ai/verifiers/tree/main/environments/mcp_env\">\n<img src=\"https://img.shields.io/badge/GitHub-181717?style=for-the-badge&logo=github&logoColor=white\" alt=\"Source Code\">\n</a>\n\n### Overview\n\n- **Environment ID**: `mcp-search-env`\n- **Short description**: Example environment using `vf.MCPEnv` for MCP server integration\n- **Tags**: MCP, Tools\n\nThis environment demonstrates how to use the first-class `MCPEnv` from `verifiers.envs.experimental`.\n\n### Datasets\n\n- **Primary dataset(s)**: N/A\n- **Source links**: N/A\n- **Split sizes**: N/A\n\n### Task\n\n- **Type**: <multi-turn | tool use>\n- **Rubric overview**: N/A\n\n### Quickstart\n\nRun an evaluation with default settings:\n\n```bash\nprime eval run mcp-search-env\n```\n\nConfigure model and sampling:\n\n```bash\nprime eval run mcp-search-env   -m gpt-4.1-mini   -n 1 -r 1\n```\n\nNotes:\n\n- Use `-a` / `--env-args` to pass environment-specific configuration as a JSON object.\n\n### Environment Arguments\n\nDocument any supported environment arguments and their meaning. Example:\n\n| Arg            | Type | Default | Description                            |\n| -------------- | ---- | ------- | -------------------------------------- |\n| `max_examples` | int  | `-1`    | Limit on dataset size (use -1 for all) |\n\n### Metrics\n\n| Metric         | Meaning                                       |\n| -------------- | --------------------------------------------- |\n| `reward`       | Main scalar reward (weighted sum of criteria) |\n| `judge_reward` | LLM judge score (1.0 if correct, 0.0 if not)  |\n","encoding":"utf-8","truncated":false,"total_bytes":1585},"status":null}