conapesca-db-mcp
MCP server for querying the CONAPESCA historical fishing landings database (2001–2026) from Mexico's Pacific and Gulf coasts, providing tools to extract and analyze standardized landing records (avisos de arribo).
README
conapesca-db-mcp
MCP server for querying the CONAPESCA historical landings database (2001–2026), covering both the Pacific and Gulf coasts of Mexico.
Exposes tools for extraction and consultation of standardized fishing landings data (avisos de arribo).
Tools available
Data access (raw extraction)
| Tool | Description |
|---|---|
get_estados(year?) |
States with landings, optional year filter |
get_species(year?, estado?, tipo_aviso?, top_n?) |
Species list with total weight and value |
species_count() |
Unique scientific names classified by taxonomic level |
get_landings(year?, estado?, especie?, tipo_aviso?, oficina?, limit?, group_by?) |
Landing records or aggregates; group_by: "year", "estado", "litoral" |
get_offices(estado?) |
CONAPESCA offices with record counts |
get_taxonomy(especie) |
Taxonomy + FishBase traits for a species |
Reporting (summaries)
| Tool | Description |
|---|---|
landings_by_year(estado?, tipo_aviso?) |
Annual totals: weight, value, species count |
landings_by_estado(year?, tipo_aviso?) |
Totals by state |
landings_by_fleet_type(year?) |
MAYORES vs MENORES vs COSECHA |
Core
| Tool | Description |
|---|---|
health_check() |
DB connectivity check |
schema_snapshot() |
Column names, types, row count |
Quick start (development)
1. Install
pip install -e ".[dev]"
2. Load dev data (SQLite)
python scripts/load_dev_data.py \
--csv /path/to/conapesca_landings_2001_2026.csv \
--db dev/conapesca_dev.sqlite \
--rows 200000 # optional sample for fast testing
3. Configure
cp .env.example .env
# .env already has USE_SQLITE=true by default
4. Run
python -m mcp_server
Production (MySQL)
Set in .env:
USE_SQLITE=false
CONAPESCA_DB_HOST=...
CONAPESCA_DB_USER=...
CONAPESCA_DB_PASSWORD=...
CONAPESCA_DB_NAME=...
The table expected in MySQL is conapesca_landings_historical with the same schema
as the pipeline output.
Resources
conapesca://data-dictionary— full column descriptionsconapesca://coverage— temporal and geographic coverage notes
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