OutdoorIQ MCP — Outdoor Recreation Intelligence

Powered by 72,000+ US lakes and 293,000+ stocking events across 12 states.

OutdoorIQ MCP is a paid MCP server that exposes lake conditions, fish-stocking records, fishing-favorability scoring, and live weather to AI agents. It is built on the CastIQ dataset (the same data that powers fishing-seo.pages.dev and the CastIQ catalog APIs).

If you're building a trip-planning assistant, a fishing app, a travel concierge, or an outdoor-brand agent that needs to recommend lakes, time visits to recent stocking events, or pull a fishing report on demand, this is the data layer you wire up.

For consumer-facing AI products, OutdoorIQ replaces a ten-source ETL with one authenticated MCP endpoint — and bills predictably so you don't get a surprise S3 invoice the first weekend traffic spikes.

Pricing

Listing & checkout: https://mcpize.com/outdooriq-mcp

Related MCP server: Weather MCP Server

Install in Claude

Live URL: https://mcp.castiq.net/mcp (Railway fallback: https://web-production-9b8950.up.railway.app/mcp)

The fastest path uses mcp-remote as a stdio→HTTP bridge:

claude mcp add outdooriq-mcp -- npx -y mcp-remote \
  https://mcp.castiq.net/mcp \
  --header "X-API-Key:outdooriq-dev-key-001"

Or configure manually:

{
  "mcpServers": {
    "outdooriq-mcp": {
      "url": "https://mcp.castiq.net/mcp",
      "headers": { "X-API-Key": "outdooriq-dev-key-001" }
    }
  }
}

Anthropic MCP Registry entry: io.github.bch1212/outdooriq-mcp — listed at https://registry.modelcontextprotocol.io.

Example agent prompt:

"Find top 5 trout lakes near Chicago for this weekend."

The agent calls get_nearby_lakes (lat/lng of Chicago, radius 200mi), filters for species: trout via get_top_lakes, then pulls get_fishing_report_summary for the top match.

Tool Reference

Architecture

client (Claude / agent)
        │  HTTP POST /mcp  (JSON-RPC 2.0)
        ▼
   FastAPI app (server.py)
        │  X-API-Key auth + per-day rate limiter
        ▼
  Tool registry (10 tools)
        │
        ▼
  db.connection.py  ──────┐
        │ Postgres mode  │  → CastIQ Postgres (72k lakes, 293k stockings)
        │ SQLite fallback│  → bundled seed (100+ lakes, ~150 stockings)
        ▼
  tools.* (lakes, stocking, scoring, weather, reports)
        │
        ▼
  Open-Meteo (no key)

Postgres vs SQLite mode

The server picks a backend at startup:

1. If DATABASE_URL is set, it tries asyncpg.create_pool. On success → logs [OutdoorIQ] Running in Postgres mode.

2. If the pool fails (timeout, bad creds, DB down) or DATABASE_URL is unset, the server seeds an in-memory SQLite DB with 100+ real lakes and logs [OutdoorIQ] Running in SQLite fallback mode.

The server always starts, regardless of Postgres availability.

Local development

git clone <this repo>
cd mcp-outdoors
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

# Run with SQLite fallback (no DATABASE_URL needed)
python -m run

# OR run against the CastIQ Postgres
export DATABASE_URL=postgresql://vikinetic:vikinetic_dev@localhost:5444/vikinetic
python -m run

Then:

curl -s http://localhost:8080/health
curl -s -X POST http://localhost:8080/mcp \
  -H "X-API-Key: outdooriq-dev-key-001" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

Tests

pytest -v

The test suite covers both the SQLite fallback path and the Postgres dispatch path (via a mocked asyncpg pool), plus auth, rate limits, all 10 tools, JSON-RPC initialize / list / call, and the scoring algorithm's bucket math.

Deploy to Railway

A deploy.sh script is included at the repo root. Run it on your Mac (the Cowork sandbox can't reach Railway/Stripe/Cloudflare APIs):

./deploy.sh

It expects RAILWAY_API_TOKEN (or RAILWAY_TOKEN exported as RAILWAY_API_TOKEN), points the project at nixpacks.toml, and sets the DATABASE_URL env var if you've also provisioned the CastIQ Postgres on Railway.

Railway gotcha (already handled): Railway exec's startCommand without a shell, so $PORT doesn't expand. We use python -m run and read PORT from os.environ inside run.py.

MCPize listing copy

OutdoorIQ MCP — the data layer for outdoor-rec AI agents. 72,000+ US lakes, 293,000+ fish-stocking events, and live weather behind one authenticated endpoint. Search lakes by name, state, or acreage; pull stocking history filtered by species and month; compute a 0-100 fishing-favorability score that bakes in recency, species diversity, lake size, and current conditions. One JSON-RPC call replaces a multi-source ETL.

Built for fishing apps, trip-planning assistants, travel concierges, and outdoor-brand agents. $14/mo Pro for unlimited use, or pay $0.01 per call. Free dev tier (50 calls/day) lets you ship a prototype before opening your wallet. Install with claude mcp add outdooriq-mcp --url https://mcp-outdoors.up.railway.app/mcp.

License

MIT. See LICENSE.