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Statistically rigorous weather and climate context: forecast plus 35-year historical ranking.
Statistically rigorous weather and climate context: forecast plus 35-year historical ranking.
Valid MCP server (1 strong, 4 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.
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Set these up before or after installing:
Environment variable: BASELINE_API_URL
Environment variable: BASELINE_API_KEY
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-elninyo-ops-baseline-mcp": {
"env": {
"BASELINE_API_KEY": "your-baseline-api-key-here",
"BASELINE_API_URL": "your-baseline-api-url-here"
},
"args": [
"baseline-mcp"
],
"command": "uvx"
}
}
}From the project's GitHub README.
MCP server exposing Baseline as agent tools — statistically rigorous weather and climate context, not just current conditions. Thin translation layer only: no climate logic lives here, every tool call is an HTTP request to the Baseline API. See baseline_mcp_server_plan.md in the Baseline project for the full design, and METHODOLOGY.md for how the underlying data and rankings are computed.
get_climate_context — natural-language weather and climate questions, full context back (forecast + 35-year historical percentile ranking).get_context_for_coordinates — same, for an exact lat/lon rather than a place name.get_water_year_status — precipitation/temperature status since the start of the water year (Oct 1 US / Jan 1 elsewhere), ranked against 35 years.compare_to_normal — how unusual current or forecast conditions are at one location.compare_locations — rank precipitation or temperature across 2-10 locations (or a curated category like colorado_ski_resorts) in a single call.Requires a Baseline API key. Self-serve signup isn't available yet — during this early period, contact Chad McNutt (chadmcnutt@gmail.com) for a key.
pip install baseline-mcp
# or: uvx baseline-mcp
Then add it to your MCP client's config, with your API key:
Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"baseline": {
"command": "uvx",
"args": ["baseline-mcp"],
"env": {
"BASELINE_API_URL": "https://api.baseline.example",
"BASELINE_API_KEY": "your-key-here"
}
}
}
}
Claude Code: claude mcp add baseline --env BASELINE_API_URL=https://api.baseline.example --env BASELINE_API_KEY=your-key-here -- uvx baseline-mcp
Cursor (.cursor/mcp.json or global MCP settings): same shape as the Claude Desktop config above, under whatever key Cursor's MCP settings use for server name.
The venv lives outside this directory (~/.venvs/baseline-mcp) rather than in .venv/ here, because this project sits under iCloud-synced ~/Documents — iCloud evicts/re-materializes files inside large venvs unpredictably, which causes intermittent ModuleNotFoundErrors. Keep it that way.
python3 -m venv ~/.venvs/baseline-mcp
~/.venvs/baseline-mcp/bin/pip install -e .
cp .env.example .env # fill in BASELINE_API_URL and a free_api-tier BASELINE_API_KEY
Run against a local Baseline instance (python3 app.py in ../baseline), then:
~/.venvs/baseline-mcp/bin/mcp dev src/baseline_mcp/server.py
All 5 tools built and tested against a live local Baseline instance, including tool-selection validation in Claude Desktop. METHODOLOGY.md (trust collateral) complete. See baseline_mcp_server_plan.md in the Baseline project for full task history. Published to PyPI as of 0.1.0.
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