Server data from the Official MCP Registry
Local MCP access to Stochastly desktop nodes, diagnostics and research tools.
About
Local MCP access to Stochastly desktop nodes, diagnostics and research tools.
Security Report
Valid MCP server (1 strong, 1 medium validity signals). 4 known CVEs in dependencies (0 critical, 3 high severity) Package registry verified. Imported from the Official MCP Registry.
3 files analyzed · 5 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
What You'll Need
Set these up before or after installing:
Environment variable: STOCHASTLY_MCP_SCRIPT
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"com-stochastly-desktop": {
"env": {
"STOCHASTLY_MCP_SCRIPT": "your-stochastly-mcp-script-here"
},
"args": [
"stochastly-mcp"
],
"command": "uvx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
Stochastly MCP
This small public launcher connects an MCP client to the server shipped with the Stochastly desktop app. The app must be installed, running, and licensed for Atelier or Portfolio. The package contains no Stochastly engine code.
Install with pip install stochastly-mcp or run with uvx stochastly-mcp. To run this source instead of the PyPI release, install this directory with pip install ..
Configure a local stdio server with command stochastly-mcp and no arguments:
- Claude Desktop: add
"stochastly": {"command": "stochastly-mcp"}undermcpServersinclaude_desktop_config.json. - Cursor: add the same entry under
mcpServersin.cursor/mcp.json. - VS Code: add
"stochastly": {"type": "stdio", "command": "stochastly-mcp"}underserversin.vscode/mcp.json.
The server exposes 29 tools, among them node_catalog, compose_graph, backtest_graph, red_flag_check, adversarial_check, portfolio_combine and export_paper. The installed app runs them and checks the licence on every call: portfolio_combine needs Portfolio, every other tool Atelier or Portfolio.
Without the app, the launcher lists the same 29 tools (names, descriptions, input schemas and annotations from stochastly_mcp_data/tools_manifest.json, generated from the app's server), so a client can see what the server offers. Each description then starts with a note that the desktop app is required, and every call to a listed tool returns a structured answer with ok: false, the edition needed and a link to request access. A name the server does not list returns the error Unknown tool, as the app's server does. The manifest is metadata only.
For a nonstandard installation, set STOCHASTLY_MCP_SCRIPT to the installed app's stochastly_mcp.py. This is a local path, not a network endpoint.
Links
- MCP server overview: what the server does and which clients it supports.
- MCP server reference: the 29 tools, their inputs and which ones write.
- Documentation: the Stochastly desktop app, from data import to research papers.
- Comparison with other backtesting tools: how Stochastly differs from other backtesting software.
- Request access: early access to the desktop app.
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