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Provides smart URL navigation to ANSYS Fluent documentation, enabling AI assistants to quickly find relevant help pages and manual sections.
Provides smart URL navigation to ANSYS Fluent documentation, enabling AI assistants to quickly find relevant help pages and manual sections.
A Model Context Protocol (MCP) server that helps AI assistants navigate ANSYS Fluent online documentation efficiently.
Choose your MCP client below for setup instructions:
claude mcp add fluent -- uvx fluent-mcp-server
Verify:
claude mcp list
claude mcp info fluent
Add to your Claude Desktop config file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json
{
"mcpServers": {
"fluent": {
"command": "uvx",
"args": ["fluent-mcp-server"]
}
}
}
Restart Claude Desktop completely after saving.
Go to Cursor Settings → MCP → Add new MCP Server:
fluentuvx fluent-mcp-serverOr edit config file:
macOS: ~/Library/Application Support/Cursor/mcp_config.json
Windows: %APPDATA%\Cursor\mcp_config.json
Linux: ~/.config/Cursor/mcp_config.json
{
"mcpServers": {
"fluent": {
"command": "uvx",
"args": ["fluent-mcp-server"]
}
}
}
CLI:
code --add-mcp '{"name":"fluent","command":"uvx","args":["fluent-mcp-server"]}'
Or add to VS Code settings:
{
"github.copilot.chat.mcp.servers": {
"fluent": {
"command": "uvx",
"args": ["fluent-mcp-server"]
}
}
}
Install Cline extension, then add to VS Code settings:
{
"cline.mcpServers": {
"fluent": {
"command": "uvx",
"args": ["fluent-mcp-server"]
}
}
}
Reload VS Code window after saving.
For 11 additional clients (Windsurf, Continue, Amp, Codex, Gemini CLI, Goose, Kiro, LM Studio, opencode, Qodo Gen, Warp), see Complete Setup Guide →
# Clone the repository
git clone https://github.com/your-org/fluent-mcp-server.git
cd fluent-mcp-server
# Install with uv
uv pip install -e ".[dev]"
# Run tests
uv run pytest
# Run server
uv run fluent-mcp-server
Development configuration (.mcp.json in project root):
{
"mcpServers": {
"fluent": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/fluent-mcp-server",
"run",
"fluent-mcp-server"
]
}
}
}
search_helpFind ANSYS Fluent documentation URLs for your query. Returns search URLs and suggested manual sections.
Parameters:
query (required): Search term (e.g., "flamelet model", "read case", "turbulence")max_suggestions (optional): Maximum manual section suggestions (default: 3)Returns:
Example:
search_help("flamelet model")
# Returns:
# - Search URL: https://ansyshelp.ansys.com/search?q=flamelet+model
# - Suggested: flamelet User Guide + Theory Guide
# - All manuals: User Guide, TUI, Theory, UDF
search_help("read case")
# Returns URLs to file/read-case TUI documentation
list_topicsList the 35+ topics with pre-mapped documentation routes.
Returns: List of topics like: file, turbulence, combustion, flamelet, mesh, boundary, udf, etc.
Example:
list_topics()
get_manual_linkGet direct link to a specific Fluent manual or section.
Parameters:
manual (required): Manual name (user_guide, tui, theory, udf)section (optional): Section path (e.g., "turbulence", "file/read-case")Example:
get_manual_link("udf", "introduction")
# Returns: https://ansyshelp.ansys.com/.../flu_udf/introduction.html
You: How do I use the flamelet model in Fluent?
Claude: [Calls search_help("flamelet model")]
[Receives URLs to flamelet documentation]
[Uses WebFetch to read the actual documentation]
[Provides answer based on official ANSYS docs]
You: Show me the command to read a case file
Claude: [Calls search_help("read case")]
[Gets URL to file/read-case TUI command]
[Retrieves documentation and shows syntax]
User Query → MCP search_help → Returns URLs →
LLM uses WebFetch → Reads official docs → Answers user
The MCP server acts as a smart navigator, not a content database.
fluent-mcp-server/
├── src/fluent_mcp_server/
│ ├── server.py # FastMCP server & tool definitions
│ ├── doc_finder.py # Smart URL router (35+ topic mappings)
│ └── __init__.py
├── md-files/
│ ├── ARCHITECTURE.md # Technical architecture
│ └── ...
├── tests/ # Unit tests
├── examples/ # Usage examples
└── pyproject.toml # Project configuration
Phase 1.x: Route Expansion (Future)
Phase 2: PyFluent Integration (Planned)
Phase 3: Workflow Automation (Planned)
See md-files/ARCHITECTURE.md for detailed roadmap.
Getting Started:
Technical Documentation:
Validation & Analysis:
Development:
MIT License
Contributions welcome! Please ensure:
uv run pytestВыполни в терминале:
claude mcp add fluent-mcp-server -- npx Web content fetching and conversion for efficient LLM usage.
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
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