Brahe Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Brahe Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
<p align="center"> <a href="https://github.com/duncaneddy/brahe-mcp/actions/workflows/test.yml/badge.svg"> <img src="https://github.com/duncaneddy/brahe-mcp/actions/workflows/test.yml/badge.svg" alt="Tests"> </a> <a href="https://pypi.org/project/brahe-mcp/"> <img src="https://img.shields.io/pypi/v/brahe-mcp" alt="PyPI"> </a> </p>
This project provides a Model Context Protocol (MCP) server that exposes the astrodynamics capabilities of the Brahe library enabling language models to get smarter about astrodynamics and space situational awareness.
demo
Recent additions expose more of brahe's 1.7.0 astrodynamics surface as MCP tools:
| Group | Tools | Notes |
|---|---|---|
| Frame transforms | list_frame_options, transform_frame | Position/state/rotation transforms across GCRF, ITRF, EME2000, GSE, EMR, SER, EMBI, SSBI, lunar (LCI/LFME/LFPA), Mars (MCI/MCMF), the Synodic rotating frame, and generic body frames. |
| SPICE & body ephemerides | list_ephemeris_options, list_spice_kernels, load_spice_kernel, load_common_spice_kernels, unload_spice_kernel, get_body_state | Manage SPICE kernels and query planet/Moon/Sun/barycenter states via SPICE. |
| Small bodies | list_smallbody_options, lookup_small_body, get_small_body_ephemeris | Look up asteroids/comets via the JPL Small-Body Database (SBDB) and sample ephemerides generated on demand via JPL Horizons. Both make live JPL network calls. |
| 3D plots | plot_trajectory_3d, plot_synodic_3d | Interactive 3D trajectory plots about Earth or in a synodic (rotating two-body) frame; each returns an inline PNG plus a saved interactive HTML file. |
| RA/Dec coordinates | list_radec_options, convert_radec, apply_proper_motion | Right ascension/declination to inertial (ECI/GCRF) and topocentric (AZEL) frames, plus IAU SOFA proper-motion propagation. Proper motion is in mas/yr; pm_ra is the cos(dec)-weighted catalog convention. |
| Orbital elements | convert_equinoctial, convert_mean_osculating, convert_mean_osculating_batch | Equinoctial elements (with retrograde factor fr) and mean/osculating conversion via Brouwer-Lyddane or numerical windowed averaging. |
| Relative motion | list_relative_motion_options, convert_rtn_state, convert_roe_state, compute_rtn_rotation | RTN and quasi-nonsingular ROE conversions between a chief and deputy satellite. |
| Attitude | list_attitude_options, convert_attitude, axis_rotation_matrix, compose_rotations, quaternion_slerp | Quaternion, Euler axis, Euler angle, and rotation matrix representations, principal-axis rotations, composition, and spherical interpolation. |
propagate_numerical supports non-Earth central bodies via the body-specific force model presets (lunar_default, mars_default, cislunar_default), or by setting force_model="central_body" with central_body set to moon, mars, or emb; the bci/bcbf output frames report state relative to that body. (central_body is only consulted for the central_body preset — other presets bake in their own body.) Two optional structured config dicts also replace the previous per-force keyword arguments:
force_config: {gravity, drag, srp, third_body, tides, relativity, frame_transform}integrator: {preset, method, abs_tol, rel_tol, initial_step, max_step, store_accelerations}Call list_propagation_options() to discover the valid keys and values for both dicts.
convert_mean_osculating handles a single state using the Brouwer-Lyddane analytical theory. convert_mean_osculating_batch handles a time series and additionally supports the numerical windowed-averaging method.
Two things to know about the numerical method:
edge="truncate" (the default), osculating-to-mean returns **fewerstates than it receives**, because the averaging window consumes the edges of the series. Read n_output and dropped_by_edge_handling from the response rather than assuming the length is preserved.
Numerical mean-to-osculating inverts the averaging by differential correction and therefore requires a force_config; call list_propagation_options() for the valid keys. Brouwer-Lyddane is a first-order theory, so mean-to-osculating followed by osculating-to-mean does not return the input exactly.
Plotting depends on the brahe[plots] extra, which is installed automatically as a dependency of brahe-mcp. The 3D plot tools also write an interactive HTML file to disk; the directory is configurable via the BRAHE_MCP_OUTPUT_DIR environment variable (default <tempdir>/brahe-mcp-plots).
uv tool install brahe-mcpor
pip install brahe-mcpThen configure your MCP client to use the installed tool:
{
"mcpServers": {
"brahe": {
"command": "brahe-mcp"
}
}
}The MCP configuration location depends on your client. For popular tools you can find it here:
| Client | Config Location |
|---|---|
| Claude Desktop (macOS) | ~/Library/Application Support/Claude/claude_desktop_config.json |
| Claude Desktop (Windows) | %APPDATA%\Claude\claude_desktop_config.json |
| Claude Code | .claude/settings.json (project-level or global) |
| Gemini CLI | ~/.gemini/settings.json |
| OpenAI Codex CLI | ~/.codex/config.toml (see below) |
[!NOTE] ChatGPT Desktop does not support local stdio MCP servers — it requires remote HTTPS endpoints
Codex CLI stores MCP configuration in TOML format at ~/.codex/config.toml (or project-scoped .codex/config.toml):
[mcp_servers.brahe]
command = "brahe-mcp"
args = []You can also add it via the CLI:
codex mcp add brahe -- brahe-mcpTo include SpaceTrack credentials:
codex mcp add brahe --env [email protected] --env SPACETRACK_PASS=your-password -- brahe-mcpThe SpaceTrack tools require a Space-Track.org account. Add your credentials via the env key in the server config:
{
"mcpServers": {
"brahe": {
"command": "brahe-mcp",
"env": {
"SPACETRACK_USER": "[email protected]",
"SPACETRACK_PASS": "your-password"
}
}
}
}[!NOTE] Claude Desktop does not expand shell variables like${SPACETRACK_USER}— you must put the actual values in the config. Claude Code inherits your shell environment, so you can alternatively set the variables in~/.zshrcand omit theenvblock.
Without these variables, the CelesTrak tools will still work normally — only the SpaceTrack tools will return an error prompting you to set the credentials.
To run the server from a local clone (useful for development or testing before installing):
git clone https://github.com/duncaneddy/brahe-mcp.git
cd brahe-mcp
uv sync --group devThen configure your MCP client to launch the server via uv run. Add the following to your MCP settings file:
{
"mcpServers": {
"brahe": {
"command": "uv",
"args": ["run", "--directory", "/path/to/brahe-mcp", "brahe-mcp"]
}
}
}Replace /path/to/brahe-mcp with the absolute path to your local clone.
uv sync --group dev
uv run pytest tests/~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.