Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"oj-mcp-server","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# Online Judge MCP Server  [](https://pypi.org/project/oj-mcp-server/) [](https://github.com/wangicheng/oj-mcp-server/blob/main/LICENSE) <a href="https://glama.ai/mcp/servers/@wangicheng/oj-mcp-server"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@wangicheng/oj-mcp-server/badge" /> </a> This is a Model Context Protocol (MCP) server that provides AI agents with tools to interact with an Online Judge API. ## Features Provides the following tools: - `list_problems(offset, limit)`: List available problems on the OJ. - `list_my_submissions(offset, limit)`: List recent submissions made by the authenticated user. - `get_problem_details(problem_id)`: Fetch detailed descriptions, samples, limits, and rules of a problem. - `submit_code(problem_id, code, language)`: Submit source code to a specific problem. - `get_submission_status(submission_id)`: Check the polling status of a code submission. ## Quickstart ### Using `uvx` (Recommended) The easiest way to run this server is using [`uvx`](https://docs.astral.sh/uv/), which automatically downloads the correct Python version, creates an ephemeral environment, and runs the tool seamlessly: ```bash set OJ_URL="http://localhost:8000" # Replace with actual OJ URL set OJ_USERNAME="your-username" set OJ_PASSWORD="your-password" uvx oj-mcp-server ``` ### Using `pip` or `pipx` Alternatively, you can install the package directly into your Python environment: ```bash pip install oj-mcp-server oj-mcp-server ``` ## Usage with MCP Clients To use this server, add it to your MCP client's configuration (e.g., Claude Desktop, Cursor, Cline). ### Claude Desktop Add the following to your `claude_desktop_config.json`: ```json { "mcpServers": { "oj-mcp-server": { "command": "uvx", "args": ["oj-…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.