jsbsim-mcp

jsbsim-mcp

Provides the JSBSim flight-dynamics engine as an MCP service, enabling AI agents to control and simulate aircraft in real-time through natural language.

Category
Visit Server

README


title: jsbsim-mcp emoji: ✈️ colorFrom: blue colorTo: indigo sdk: docker app_port: 7860 app_file: app.py pinned: false license: apache-2.0 short_description: JSBSim flight-dynamics engine as a self-hosted MCP service

jsbsim-mcp — Self-Hosted MCP Service

JSBSim flight dynamics, exposed as an MCP service you run locally. Bring your own compute — pip install or docker run, plug into any MCP-aware agent.

This is the Self-Hosted distribution of jsbsim-mcp. It is not a hosted endpoint — you deploy it locally and bind it as an MCP stdio server to Claude Desktop / Claude Code / Cursor / Codex.

For the deployed hosted version, see the HF Space mirror (separate project).


1. Install

Option A — pip (recommended for Claude Desktop / Cursor / Codex)

pip install -e .
# or:
# pip install git+https://github.com/flyintothesky/jsbsim-mcp.git

Requires Python ≥ 3.10 and jsbsim == 1.3.1.

Option B — Docker (recommended for sandboxing)

docker build -t jsbsim-mcp .
docker run --rm -it jsbsim-mcp stdio

Option C — From this repo

git clone https://github.com/flyintothesky/jsbsim-mcp
cd jsbsim-mcp
pip install -r requirements.txt
python -m scripts.slim_data    # optional, ~24 MB → saves MB
python run_stdio.py

2. Wire into Claude Desktop / Cursor / Codex

claude_desktop_config.json (or its equivalent for your client):

{
  "mcpServers": {
    "jsbsim-fdm-local": {
      "command": "python",
      "args": ["/abs/path/to/jsbsim-mcp/run_stdio.py"]
    }
  }
}

Restart Claude. Tools list appears:

list_aircraft        create_session      close_session
set_initial_conditions    trim           step
get_property        set_property        get_telemetry
execute_script

3. (Optional) Run the bundled web dashboard

Want a browser UI for the simulation? Run the same code as an HTTP server:

python app.py      # → http://localhost:7860/
  • Live PFD
  • 3D attitude indicator
  • Time-series charts (altitude / speed / alpha / thrust)
  • WebSocket telemetry at ~20 Hz
  • Browser-side MCP JSON-RPC console

Works inside Docker as well:

docker run --rm -p 7860:7860 jsbsim-mcp
# then visit http://localhost:7860/

4. Tool reference (10 tools)

Tool Summary
list_aircraft List 60+ bundled aircraft names
create_session Spin up a session, return session_id
close_session Tear it down
set_initial_conditions Apply altitude / airspeed / heading etc.
trim Iteratively balances elevator for level flight
step Advance N simulated seconds
get_property Read any JSBSim property by path
set_property Write any JSBSim property
get_telemetry One-shot 40+ scalar frame
execute_script Load a <run> JSBSim script

Full schema: docs/API.md.

5. Architecture

src/engine/    JSBSim wrapper + session pool + telemetry
src/server/    MCP protocol adapter (FastMCP, stdio + HTTP)
src/dashboard/ FastAPI dashboard + WebSocket broadcaster
app.py         Combined ASGI dispatcher (HTTP + WS + MCP)
run_stdio.py   Stdio entry for local Claude clients

LGPL-2.1 boundary preserved (JSBSim is dynamically linked). See THIRD_PARTY_NOTICES.md.


Why Self-Hosted?

JSBSim's open-source license permits redistribution, but the model files (60 aircraft, ~30 MB) and C++ simulator itself are heavy. The practical way to consume this in agents is:

  1. pip install once.
  2. Run per-developer as an MCP server via stdio.
  3. Optionally start the dashboard for human-in-the-loop.

This avoids round-tripping 60 aircraft over a public MCP endpoint and keeps your proprietary IC files local.

If you want a centrally hosted version for a team, see the self-hosted Docker recipe in docs/DEPLOY_MODELSCOPE.md — point your own HF Space / Render / Fly.io at the same source.


License

  • This project: Apache-2.0
  • JSBSim dependency: LGPL-2.1

See LICENSE and THIRD_PARTY_NOTICES.md.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured