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Flox MCP

by flox-foundation

Local stdio tools for inspecting lrvx APIs, scaffolding strategies, validating code, running backtests, and analyzing indicators.

Install Flox MCP

Pick your client, then add it in one click or paste the config.

STDIOPython
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "flox-foundation-flox-mcp": {
      "command": "uvx",
      "args": [
        "lrvx-mcp"
      ],
      "env": {
        "LRVX_RUNTIME_STATE": "YOUR_VALUE_HERE",
        "LRVX_CONTROL_URL": "YOUR_VALUE_HERE",
        "LRVX_CONTROL_TOKEN": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Install not yet sandbox-tested— we haven't run this command through our automated sandbox yet. Not a red flag; we're working through the catalog.

Overview

flox-foundation/flox-mcp MCP server gives AI clients local, grounded access to the lrvx trading framework’s API snapshots, bindings, documentation, examples, indicators, and strategy templates. It runs as a child process over stdio, so requests stay on the developer’s machine and the client can inspect real signatures instead of guessing. Use it when building or reviewing Python or Node strategies, exploring lrvx events and indicators, or running CSV-based backtests. Its backtest runner limits resources but does not isolate filesystem or network access, so untrusted workloads need stronger sandboxing.

Use cases

  • Inspect lrvx C API signatures before writing bindings
  • Scaffold Python or Node trading strategies
  • Validate strategy code for syntax and unsafe calls
  • Run resource-limited backtests against CSV data
  • Explore and calculate lrvx indicators

Key features

  • C API, binding, event, and error lookup
  • Python and Node strategy scaffolding
  • Static Python strategy validation
  • FTS5 documentation and example search
  • Indicator discovery and calculation
  • CSV backtesting with resource caps

Tools13

What Flox MCP lets your agent do. Expand a tool for its parameters.

Self-reported~585 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

22/22 checks healthy over the last 82d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 12d ago via OSV.dev · lrvx-mcp (PyPI)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars229Stargazers on the source repository.
Last commit1d agoMost recent push to the default branch.
Tools exposed13Callable tools this server registers over MCP.
Directory activity5 viewsConfig copies, upvotes, and views on AllMCPs.

How Flox MCP works

What flox-foundation/flox-mcp MCP server does

flox-foundation/flox-mcp exposes reference and development tools for the lrvx trading systems framework. Its bundled data covers the C API, binding symbol maps, error pages, strategy examples, and a searchable documentation index. The server also provides indicator introspection, strategy templates, static validation, and a backtest entry point.

Most operations inspect packaged, read-only data. The server can execute indicator calculations and launch Python backtests, but these capabilities have different execution boundaries and should be treated accordingly.

How it works

An MCP client starts the server locally as a child process and communicates with it through stdio. There is no public hosting layer or server-side network service. The package can be installed with pip, after which lrvx-mcp init writes an MCP configuration for the project. The generated configuration launches lrvx-mcp serve.

The reference tools read versioned snapshots and indexes packaged with the wheel. The C API lookup uses the committed ABI snapshot, while symbol and binding queries use an IR-derived map. Documentation search uses an FTS5 SQLite index built from selected documentation roots. Strategy scaffolds are checked before delivery: Python templates are parsed and validated, and Node templates pass node --check.

Setup and configuration

Install the package with:

Terminal
pip install lrvx-mcp
lrvx-mcp init

Restart the MCP client after initialization. The initializer can write a project configuration, target a global Claude configuration, print the merged configuration instead of writing it, or replace an existing entry with --overwrite.

For indicator calculation, install the optional lrvx dependency:

Terminal
pip install "lrvx-mcp[lrvx]"

An engine simulation can provide control settings for additional runtime state tools. Start lrvx engine sim, then pass its URL and token to lrvx-mcp init --overwrite using --engine-url and --token. The resulting configuration can set LRVX_RUNTIME_STATE, LRVX_CONTROL_URL, and LRVX_CONTROL_TOKEN.

Tools and capabilities

  • Inspect indicators with list_indicators, calculate one with compute_indicator, or rank candidates with the keyword-based suggest_indicator tool.
  • Search the C API and binding exports using list_capi_functions and list_bindings.
  • Translate names across C, Python, Node, and Codon with lookup_symbol.
  • Decode supported event structures or raw event dictionaries through explain_event.
  • Find error explanations with lookup_error_code and search indexed documentation with docs_search.
  • Retrieve language-filtered examples with get_example.
  • Generate bar-driven, trade-driven, or hybrid Python and Node strategy starters using scaffold_strategy.
  • Check Python strategy syntax, required hooks, and forbidden eval or exec calls with validate_strategy.
  • Run a Python strategy against CSV data with run_backtest, using CPU, memory, output, and wall-clock limits.

Limitations and notes

The backtest subprocess is an MVP sandbox. It limits resources but does not isolate filesystem or network access, so production use with untrusted Python should add nsjail, firejail, Docker, or an equivalent isolation layer. suggest_indicator uses keyword matching rather than an LLM and its result should be checked with list_indicators. The server’s local stdio design keeps requests on the machine, but it does not by itself provide stronger isolation for code execution.

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Frequently Asked Questions about Flox MCP

flox-foundation/flox-mcp is an MCP server that connects AI clients to the lrvx trading framework through local stdio. Its main tools inspect C API and binding symbols, search documentation, scaffold and validate strategies, discover and compute indicators, explain events, and run resource-limited Python backtests against CSV data.

Install it with pip, then initialize an MCP configuration using `pip install lrvx-mcp` and `lrvx-mcp init`. The initializer writes a project-local configuration by default; restart the MCP client afterward. Use `--global`, `--print`, or `--overwrite` when those configuration behaviors are needed.

Yes, flox-foundation/flox-mcp works with Cursor through its standard local stdio configuration. Run `lrvx-mcp init` to create the project configuration, then restart Cursor. The same MCP configuration shape is also documented for Claude Code and Cline.

No, the built-in backtest runner is not a complete isolation boundary. It limits CPU, memory, output, and wall-clock time, but does not isolate filesystem or network access. Use nsjail, firejail, Docker, or comparable isolation when running untrusted Python.

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