Most callers do not need to run anything - DaedalMap is a live remote MCP server (and HTTP API) for geographic data:
- MCP endpoint:
https://app.daedalmap.com/mcp(streamable HTTP) - Start with
get_catalog, thenget_packfor a pack's metrics and a first-query example - Free packs: currency (FX rates), volcanoes, hurricanes, floods, tornadoes, UN SDG, World Factbook, WorldPop
- Paid via x402 on Base mainnet USDC: earthquakes, tsunamis (call unpaid first - the server returns the exact price before any charge)
- Agent docs:
https://daedalmap.com/docs/for-agents
The rest of this README is the self-host / local-runtime path.
DaedalMap is a map-first geographic query engine. This repository is the open app/runtime for developers who want to run it locally, self-host it, point it at their own data, or extend it with compatible geographic datasets.
Public surfaces:
- App:
https://app.daedalmap.com - Website/docs:
https://daedalmap.com
There are now two valid ways to approach DaedalMap locally:
GitHub/self-host path- use this repo directly
- best for developers, custom data work, and users who want to control setup
Downloadable launcher path- curated wrapper + engine artifact + pack install flow
- best for users who want the same runtime with less setup friction
These should stay the same product at the runtime/contract level, but they do not need identical UI on every surface.
If you are using this public GitHub repo as a self-host/local runtime, the practical setup contract right now is:
- a local data location (
DATA_ROOT, unless you use the default app-data path) - an LLM API key (
OPENAI_API_KEYorANTHROPIC_API_KEY)
Supabase and hosted account wiring are optional for self-host use.
Use this repo if you want to:
- run the DaedalMap runtime on your own machine or server
- point the runtime at local data or a cloud-backed data plane you control
- inspect or extend the open runtime behavior
- build compatible geographic datasets and pack-style workflows around the engine
Typical use cases:
- show earthquakes, floods, wildfires, storms, volcanoes, or tsunamis for a place and time window
- compare population, economic, and disaster context in the same workflow
- move between local development, self-hosted runtime operation, and hosted-style runtime behavior without changing the basic mental model
DaedalMap itself is built around three ideas:
- ask in plain language instead of assembling GIS workflows first
- keep the map as the primary interface, not an afterthought
- separate runtime delivery from maintained data-pack delivery
This repo is therefore best read as:
- the open runtime engine
- the self-host/developer entry point
- the source of truth for the downloadable engine snapshot users install through the launcher
It is not the hosted account, billing, or admin surface. Those product surfaces are separate from the public runtime and may evolve faster than the downloadable runtime UI.
If you are deciding between this repo and the downloadable launcher, use this rule of thumb:
- use the GitHub repo when you want:
- code access
- self-host setup
- custom data or custom pack work
- runtime-level experimentation
- use the downloadable launcher when you want:
- a curated install/update path
- a local Research-oriented runtime with less setup work
- pack installs and local runtime management without treating Git as the main UX
The goal is that both paths converge on the same core runtime behavior even if their setup UX differs.
If you are browsing this repository, treat it as the developer and self-host entry point.
If you want a more guided local install path, use the downloadable launcher when it is available through release/distribution channels.
In other words:
- GitHub checkout = source, self-host, customization, local development
- downloadable launcher = curated local install and runtime management
Both paths are intended to lead to the same DaedalMap runtime family.
The hosted runtime ships with 40+ curated sources across disasters, demographics, economics, and climate. Coverage below reflects the current maintained pack inventory.
| Source | Scale | Time Range |
|---|---|---|
| USGS Earthquakes | 1M+ events | 2150 BC - present |
| IBTrACS Hurricanes/Cyclones | 13K storms | 1842 - present |
| NOAA Tsunamis | 2.6K events | 2000 BC - present |
| Smithsonian Volcanoes | 11K eruptions | Holocene |
| Global Wildfires | 940K events/year | 2002 - 2024 |
| USA/CAN Tornadoes | 81K events | 1950 - present |
| Global Floods | 4.8K events | 1985 - 2019 |
| Global Landslides | 45K events | 1760 - present |
Disaster events include 22M+ geographic location relationships and 566K cross-disaster links (aftershocks, triggered events).
| Source | Countries | Years | Category |
|---|---|---|---|
| Our World in Data CO2 | 217 | 1750 - 2024 | Environment |
| WHO Health Statistics | 198 | 2015 - 2024 | Health |
| IMF Balance of Payments | 195 | 2005 - 2022 | Economy |
| UN Sustainable Development Goals | 200+ | 2000 - 2023 | SDGs 1-17 |
| Eurostat Demographics | 37 European countries | 2000 - 2024 | Demographics |
| Country | Source Count | Examples |
|---|---|---|
| USA | 15+ | Census, FEMA National Risk Index, NOAA storms |
| Canada | 3 | Statistics Canada, NRCan earthquakes, drought |
| Australia | 2 | ABS population, BOM cyclones |
Disasters are displayed with animated, type-specific rendering:
- Point + radius: earthquakes, volcanoes, tornadoes
- Track/trail: hurricanes and cyclones
- Radial wave: tsunamis
- Polygon fill: wildfires, floods
DaedalMap now treats runtime behavior as a 2-axis matrix:
INSTALL_MODElocal= local app/runtime installcloud= hosted/server deployment
RUNTIME_MODElocal= query local datacloud= query managed cloud-backed data via local cache + DuckDB httpfs
Supported combinations:
local install + local datalocal install + cloud datacloud install + cloud data
Not supported as a first-class runtime shape:
cloud install + local data
The current hosted/runtime direction is:
- a hosted app runtime
- object storage for runtime data
- optional auth and account services
In RUNTIME_MODE=cloud, the runtime:
- eagerly syncs only small metadata files to local cache
- queries parquet directly from object storage via DuckDB
httpfs - does not sync the full parquet tree at startup
Hosted deployment topology, release lanes, and operator control-plane details belong in private deployment notes.
That means the same codebase can be used in:
- full local-data mode
- hosted-style cloud-data mode
Guest users can open the app and try the public workflow without logging in.
Logged-in users currently get:
- authenticated session identity
- user-scoped frontend persistence
- user-scoped backend session cache
- account-owned settings and login on
daedalmap.com
The public app no longer owns the account/settings UI.
app.daedalmap.com stays focused on the runtime and map engine, while .com
owns login, account, billing, and admin/runtime control-plane views.
cd county-map
pip install -r requirements.txtCreate a .env file for local development. The minimum useful local setup is:
ANTHROPIC_API_KEY=your_key_here
DATA_ROOT=C:/path/to/your/local/dataYou can use OPENAI_API_KEY instead of ANTHROPIC_API_KEY if that is your preferred provider.
If you leave DATA_ROOT blank, DaedalMap uses the default local app-data path and expects your data to live there.
Hosted-style object-storage configuration is intentionally deployment-specific. For public self-hosting, start with local data. Operators who run a cloud-backed deployment should provide their own object-storage bucket, endpoint, and credentials through environment variables.
Most local users should leave these blank unless they intentionally want overrides:
DATA_ROOT=
APP_URL=
SITE_URL=What they mean:
DATA_ROOTonly used inRUNTIME_MODE=local; leave blank to use the default local app-data folderAPP_URLoptional advertised app URL; leave blank for normal local runsSITE_URLoptional website/docs/account URL override; leave blank for normal local runs
If you are configuring your own hosted deployment, set:
INSTALL_MODE=cloud
RUNTIME_MODE=cloud
PORT=7000If you want optional Supabase-backed auth locally:
SUPABASE_URL=...
SUPABASE_ANON_KEY=...Keep service-role keys server-side only. They are not needed for ordinary local evaluation.
python app.pyOpen:
http://localhost:7000
The runtime exposes discovery and query endpoints on your local instance.
Discovery (no auth, no payment):
GET /api/v1/guideGET /api/v1/catalogGET /api/v1/packs/{pack_id}
Execution:
POST /api/v1/query/dataset
Self-host instances return commercial_access_unavailable for the paid execution lane unless a commercial verifier is configured. Discovery endpoints work without additional setup.
For managed data access via the hosted API or MCP, see daedalmap.com/docs/for-agents.
The runtime resolves behavior from two explicit modes:
INSTALL_MODEcontrols deployment defaults like writable directories and default URLsRUNTIME_MODEcontrols the data plane
Data mode behavior:
RUNTIME_MODE=localusesDATA_ROOTRUNTIME_MODE=clouduses the hydrated local cloud cache asDATA_ROOT
Default local writable folders on Windows:
CONFIG_DIR=%LOCALAPPDATA%\DaedalMap\configSTATE_DIR=%LOCALAPPDATA%\DaedalMap\stateCACHE_DIR=%LOCALAPPDATA%\DaedalMap\cacheLOG_DIR=%LOCALAPPDATA%\DaedalMap\logsPACKS_ROOT=%LOCALAPPDATA%\DaedalMap\packsDATA_ROOT=%LOCALAPPDATA%\DaedalMap\data
In hosted/cloud mode:
- metadata is cached locally
- parquet is queried remotely from object storage
That makes local cloud-mode testing useful for reproducing hosted-runtime behavior before deploy.
Important note:
- the current public repo does not include a bundled
data/demo tree - a source checkout therefore needs either
DATA_ROOTinlocalmode, orRUNTIME_MODE=cloudwith cloud storage configured - for a usable chat experience, you should also set
OPENAI_API_KEYorANTHROPIC_API_KEY
The old “demo data folder plus converters” framing is no longer the whole story.
The current direction is:
- the engine stays open
- maintained data is packaged as packs
- packs are validated and promoted with explicit release gates
- runtime catalogs eventually depend on pack availability, installation, and entitlement state
Key concepts:
available packsinstalled packsentitled packsactive runtime catalog
These are intentionally distinct.
Explore chat and Research chat use different discovery paths:
- Explore starts from the runtime catalog, then selects sources.
- Research starts from the active corpus manifest or loaded artifacts, then selects sources.
After a specific source is selected, they should follow the same source contract:
- source-level
temporal_coverageis discovery guidance - metric-level
metrics.{metric_id}.yearsis the execution truth - default year windows, slider bounds, and metric year ranges should clamp to the selected metric when available
That shared source-specific logic now lives in mapmover/source_time_contract.py. Use that helper module for metric-aware year bounds instead of re-implementing time-range logic separately in Explore or Research code paths.
/settings now behaves differently depending on mode:
- hosted/account-aware mode: redirects to the paired account surface
- self-host/local mode: shows local runtime setup guidance
For self-host users, /settings is the in-app reminder page for:
- required LLM key setup
- current runtime/data/config paths
- the current state of local data vs future pack install flow
Important files and folders:
app.py- FastAPI app entrypointmapmover/- runtime logic, routes, path helpers, DuckDB helpersstatic/- frontend app modules and stylestemplates/- app HTML shellsupabase_client.py- auth/control-plane integrationdocs/- local documentation for schemas, runtime notes, and reference material
Public runtime docs live in docs/README.md.
Recommended starting points:
- docs/LOCAL_AND_HOSTED.md - runtime mode selection and self-host basics
- docs/DATA_SCHEMAS.md - schema and
loc_idconventions - docs/APP_OVERVIEW.md - higher-level runtime/app overview
Useful local modes:
- Full local-data mode
- points at your local
DATA_ROOT - best current self-host mode for GitHub users
- Hosted-style S3 mode
- local server, but object-storage-backed data path
- best for reproducing hosted runtime behavior before deploy
- Installed/runtime-pack mode
- planned product direction beyond raw source checkout
- engine/runtime installed separately from data packs
- pack selection and updates handled outside the repo clone flow
Questions, feedback, or self-host issues: support@daedalmap.com
MIT
If an agent or tool was pointed at this README for programmable access, use:
- Agent docs: https://daedalmap.com/docs/for-agents
- Machine-readable entry: https://daedalmap.com/llms.txt