daedal-map

daedal-map

Remote MCP server for geographic data. Free and x402 paid packs all normalized for cross domain joins. Start with get_catalog, then get_pack for details.

Category
访问服务器

README

DaedalMap

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

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_KEY or ANTHROPIC_API_KEY)

Supabase and hosted account wiring are optional for self-host use.

What This Repo Is For

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

Data Coverage

The hosted runtime ships with 40+ curated sources across disasters, demographics, economics, and climate. Coverage below reflects the current maintained pack inventory.

Global Disasters

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).

Global Indicators

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-Specific Sources

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

Disaster Display

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

Current Runtime Shape

DaedalMap now treats runtime behavior as a 2-axis matrix:

  • INSTALL_MODE
    • local = local app/runtime install
    • cloud = hosted/server deployment
  • RUNTIME_MODE
    • local = query local data
    • cloud = query managed cloud-backed data via local cache + DuckDB httpfs

Supported combinations:

  • local install + local data
  • local install + cloud data
  • cloud 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 And Logged-In Behavior

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.

Quick Start

1. Install dependencies

cd county-map
pip install -r requirements.txt

2. Add environment variables

Create 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/data

You 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_ROOT only used in RUNTIME_MODE=local; leave blank to use the default local app-data folder
  • APP_URL optional advertised app URL; leave blank for normal local runs
  • SITE_URL optional 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=7000

If 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.

3. Run the app

python app.py

Open:

  • http://localhost:7000

API Discovery

The runtime exposes discovery and query endpoints on your local instance.

Discovery (no auth, no payment):

  • GET /api/v1/guide
  • GET /api/v1/catalog
  • GET /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.

Data Resolution

The runtime resolves behavior from two explicit modes:

  1. INSTALL_MODE controls deployment defaults like writable directories and default URLs
  2. RUNTIME_MODE controls the data plane

Data mode behavior:

  1. RUNTIME_MODE=local uses DATA_ROOT
  2. RUNTIME_MODE=cloud uses the hydrated local cloud cache as DATA_ROOT

Default local writable folders on Windows:

  • CONFIG_DIR=%LOCALAPPDATA%\DaedalMap\config
  • STATE_DIR=%LOCALAPPDATA%\DaedalMap\state
  • CACHE_DIR=%LOCALAPPDATA%\DaedalMap\cache
  • LOG_DIR=%LOCALAPPDATA%\DaedalMap\logs
  • PACKS_ROOT=%LOCALAPPDATA%\DaedalMap\packs
  • DATA_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_ROOT in local mode, or RUNTIME_MODE=cloud with cloud storage configured
  • for a usable chat experience, you should also set OPENAI_API_KEY or ANTHROPIC_API_KEY

Data And Pack Direction

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 packs
  • installed packs
  • entitled packs
  • active runtime catalog

These are intentionally distinct.

Explore And Research Contract

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_coverage is discovery guidance
  • metric-level metrics.{metric_id}.years is 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 Page

/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

Useful Paths In This Repo

Important files and folders:

  • app.py - FastAPI app entrypoint
  • mapmover/ - runtime logic, routes, path helpers, DuckDB helpers
  • static/ - frontend app modules and styles
  • templates/ - app HTML shell
  • supabase_client.py - auth/control-plane integration
  • docs/ - local documentation for schemas, runtime notes, and reference material

Documentation In This Repo

Public runtime docs live in docs/README.md.

Recommended starting points:

Local Development Modes

Useful local modes:

  1. Full local-data mode
  • points at your local DATA_ROOT
  • best current self-host mode for GitHub users
  1. Hosted-style S3 mode
  • local server, but object-storage-backed data path
  • best for reproducing hosted runtime behavior before deploy
  1. 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

Contact

Questions, feedback, or self-host issues: support@daedalmap.com

License

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

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选