{"id":51495115,"url":"https://github.com/yusong652/itasca-mcp","last_synced_at":"2026-07-07T14:30:57.816Z","repository":{"id":338161123,"uuid":"1155237595","full_name":"yusong652/itasca-mcp","owner":"yusong652","description":"MCP server connecting AI agents to ITASCA engines (PFC, FLAC, 3DEC, MPoint, MassFlow) — run numerical simulations through natural conversation","archived":false,"fork":false,"pushed_at":"2026-07-04T14:13:20.000Z","size":14491,"stargazers_count":117,"open_issues_count":0,"forks_count":10,"subscribers_count":2,"default_branch":"main","last_synced_at":"2026-07-04T16:04:58.126Z","etag":null,"topics":["3dec","ai-agent","claude","claude-code","codex","dem","discrete-element-method","flac","gemini-cli","geomechanics","itasca","itasca-pfc","llm-tools","mcp","mcp-server","model-context-protocol","particle-flow-code","pfc","simulation"],"latest_commit_sha":null,"homepage":"https://pypi.org/project/itasca-mcp/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/yusong652.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":"AGENTS.md","dco":null,"cla":null}},"created_at":"2026-02-11T09:31:43.000Z","updated_at":"2026-07-04T14:12:00.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/yusong652/itasca-mcp","commit_stats":null,"previous_names":["yusong652/pfc-mcp","yusong652/itasca-mcp"],"tags_count":50,"template":false,"template_full_name":null,"purl":"pkg:github/yusong652/itasca-mcp","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yusong652%2Fitasca-mcp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yusong652%2Fitasca-mcp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yusong652%2Fitasca-mcp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yusong652%2Fitasca-mcp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/yusong652","download_url":"https://codeload.github.com/yusong652/itasca-mcp/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yusong652%2Fitasca-mcp/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35232326,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-07-07T02:00:07.222Z","response_time":90,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["3dec","ai-agent","claude","claude-code","codex","dem","discrete-element-method","flac","gemini-cli","geomechanics","itasca","itasca-pfc","llm-tools","mcp","mcp-server","model-context-protocol","particle-flow-code","pfc","simulation"],"created_at":"2026-07-07T14:30:46.712Z","updated_at":"2026-07-07T14:30:57.724Z","avatar_url":"https://github.com/yusong652.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://raw.githubusercontent.com/yusong652/itasca-mcp/assets/header.webp\" alt=\"itasca-mcp\" width=\"70%\"\u003e\n\u003c/p\u003e\n\n# itasca-mcp\n\n[English](https://github.com/yusong652/itasca-mcp/blob/main/README.md) | [简体中文](https://github.com/yusong652/itasca-mcp/blob/main/README.zh-CN.md)\n\n[![PyPI](https://img.shields.io/pypi/v/itasca-mcp)](https://pypi.org/project/itasca-mcp/)\n[![Downloads](https://static.pepy.tech/badge/itasca-mcp)](https://pepy.tech/project/itasca-mcp)\n[![GitHub stars](https://img.shields.io/github/stars/yusong652/itasca-mcp)](https://github.com/yusong652/itasca-mcp/stargazers)\n[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE)\n[![Python 3.10+](https://img.shields.io/badge/python-3.10%2B-blue)](https://www.python.org/)\n\n`itasca\u003emodel new ;now, with LLM.`\n\n**itasca-mcp** connects AI agents to [ITASCA](https://www.itascacg.com/)'s numerical modeling software — PFC, FLAC, 3DEC, MPoint, and MassFlow — through the [Model Context Protocol](https://modelcontextprotocol.io/). Browse documentation, run simulations, and execute code, all through natural conversation. Pick the engine with the `software` parameter.\n\n`itasca\u003emodel solve ;LLM solves.`\n\n![itasca-mcp demo](https://raw.githubusercontent.com/yusong652/itasca-mcp/assets/itasca-mcp.gif)\n\n## Tools (10)\n\n**5 documentation tools** — browse and search the selected engine's commands, Python API, and reference docs (`software` parameter). No bridge required.\n\n**5 execution tools** — interactive REPL, task submission, progress monitoring, interruption, and history. Requires bridge.\n\n## First-time Setup\n\n### Prerequisites\n\n- **An ITASCA engine installed** — PFC, FLAC, 3DEC, MPoint, or MassFlow. 9.0+ recommended; PFC 6.0 / 7.0 and FLAC 7.0 are also supported.\n- **[uv](https://docs.astral.sh/uv/getting-started/installation/)** installed (for `uvx`)\n\n### Agentic Setup (Recommended)\n\nCopy this to your AI agent and let it self-configure:\n\n```text\nFetch and follow this bootstrap guide end-to-end:\nhttps://raw.githubusercontent.com/yusong652/itasca-mcp/main/docs/agentic/itasca-mcp-bootstrap.md\n```\n\n### Manual Setup\n\n**1. Register the MCP server** with your agent.\n\nMost agents register it with a single command:\n\n```bash\n# Claude Code\nclaude mcp add itasca-mcp -- uvx itasca-mcp\n\n# Codex / Codex-cli\ncodex mcp add itasca-mcp -- uvx itasca-mcp\n\n# Gemini CLI\ngemini mcp add itasca-mcp uvx itasca-mcp\n```\n\nOr fill in the MCP config file manually:\n\n```json\n{\n  \"mcpServers\": {\n    \"itasca-mcp\": {\n      \"command\": \"uvx\",\n      \"args\": [\"itasca-mcp\"]\n    }\n  }\n}\n```\n\n**2. Start the bridge from inside the ITASCA engine:**\n\nDownload [`addon.py`](addon.py), then use either of these two flows inside the engine GUI (PFC, FLAC, 3DEC, ...):\n\n- Copy the file contents into the engine's IPython console and run them\n- Or download the file and execute it in the engine GUI\n\n\u003cimg src=\"https://raw.githubusercontent.com/yusong652/itasca-mcp/assets/addon.gif\" alt=\"addon.py demo\" width=\"60%\"\u003e\n\n### Verify\n\nRestart your AI agent (Claude Code, Codex CLI, Gemini CLI, etc.) and ask it to call `itasca_execute_code` to verify the connection.\n\n## Daily Startup\n\nOnce first-time setup is done, each new engine session only needs the bridge re-started — run this in the engine's IPython console and you're back online:\n\n```python\nimport itasca_mcp_bridge\nitasca_mcp_bridge.start()\n```\n\n`start()` checks PyPI for a newer bridge release and self-upgrades before starting. The MCP client config persists.\n\n## Features\n\n- **Multi-engine corpus** - command, Python API, and reference docs for PFC, FLAC, 3DEC, MPoint, and MassFlow, selected via the required `software` parameter\n- **Multi-version support** - command docs across engine versions (PFC: 6.0/7.0/9.0, FLAC: 7.0/9.0) via the `version` parameter\n- **Hierarchical documentation browsing** - agents navigate the engine command tree to discover capabilities and boundaries, reducing hallucinated commands\n- **Enhanced plot documentation** - plot items reference docs supplementing the official documentation\n- **Interactive REPL** - rapid iteration before committing to full scripts; agents can quickly test and refine code\n- **Task lifecycle management** - submit long-running simulations, monitor progress, interrupt running tasks, and browse task history\n- **Multi-client compatible** - works with Claude Code, Codex CLI, Gemini CLI, GitHub Copilot CLI, OpenCode, toyoura-nagisa, and other MCP clients\n\n## Troubleshooting\n\nSee [Troubleshooting](docs/agentic/itasca-mcp-bootstrap.md#troubleshooting) in the bootstrap guide.\n\n## Development\n\nSee [Developer Guide: Install and Run from Source](docs/development/source-install.md).\n\n\u003ca href=\"https://glama.ai/mcp/servers/yusong652/itasca-mcp\"\u003e\n  \u003cimg width=\"200\" height=\"105\" src=\"https://glama.ai/mcp/servers/yusong652/itasca-mcp/badge\" alt=\"itasca-mcp MCP server\" /\u003e\n\u003c/a\u003e\n\n## Contributing\n\nPRs and issues are welcome! See the [Developer Guide](docs/development/source-install.md) to get started.\n\n## License\n\nMIT - see [LICENSE](LICENSE).\n\n\u003c!-- mcp-name: io.github.yusong652/itasca-mcp --\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyusong652%2Fitasca-mcp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fyusong652%2Fitasca-mcp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyusong652%2Fitasca-mcp/lists"}