MCP server for Mireye Earth — federal-source-cited geospatial data for any MCP-aware agent.
Project description
mireye-mcp
Developed in a private monorepo. This repository (Mireye-Labs/mireye-earth-mcp) is the published source of the
mireye-mcpPyPI package, snapshot-synced on every release. Issues and PRs are welcome here (changes are applied upstream and re-synced; the test suite runs in the monorepo); releases land via PyPI.
Expose Mireye Earth's /v1/ask and /v1/fetch endpoints to MCP clients
that need a local stdio adapter (Claude Desktop, Cursor, custom agents
built on the mcp Python SDK) as native tools — no HTTP wiring required.
This is a standalone PyPI package (mireye-mcp) with only two
runtime dependencies — httpx and mcp. It does not pull in the
geospatial backend, so there's no GDAL / rasterio / DuckDB build step.
The server is a local stdio adapter with no geospatial business logic: tool handlers POST to the deployed Mireye HTTP API, while read-only MCP resources fetch and cache the public field catalog.
Mireye also exposes a hosted remote MCP endpoint at
https://api.mireye.com/mcp for clients that support Streamable
HTTP and native OAuth. Use that hosted endpoint for Claude Code so /mcp
opens the browser sign-in flow. This package remains the local stdio path;
it uses mireye-mcp login or MIREYE_BEARER_TOKEN for credentials.
What the agent gets
Two tools, both prefixed mireye_ so they sort together and don't
collide with generic ask / fetch tools from other MCP servers:
| Tool | When the agent should call it |
|---|---|
mireye_ask |
The caller asked a question about a US place ("is this in a flood zone?", "wildfire risk?"). |
mireye_fetch |
The caller wants specific named fields ("elevation and slope here") or is powering a workflow. |
Catalog context is exposed as MCP resources instead of extra tools:
| Resource | What it returns |
|---|---|
mireye://catalog/fields |
Full field catalog. |
mireye://catalog/presets |
Preset names and field expansions. |
mireye://catalog/us-envelope |
Supported coordinate bounds. |
mireye://field/{name} |
One field definition. |
mireye://preset/{name} |
One preset expansion. |
Workflow prompts are also registered: mireye_ask, mireye_fetch,
mireye_site_report, mireye_flood_check, mireye_wildfire_underwrite,
and mireye_pick_fields. Claude Code surfaces MCP prompts as slash
commands under the form /mcp__<server>__<prompt>.
There is no third list_fields tool. Agents that need the catalog should
read the MCP resources above; the stdio adapter backs them with
GET /v1/meta/fields and a 1-hour ETag-aware cache.
Install local stdio — one command with uvx
uvx mireye-mcp
That's it. uvx (bundled with uv)
downloads the package into a managed cache, runs the entry point, and
the next invocation is instant. No venv to manage, no pip install,
no native builds.
If you don't have uv:
curl -LsSf https://astral.sh/uv/install.sh | sh
Plain pip also works:
pip install mireye-mcp
mireye-mcp # entry point
Official MCP Registry
This server publishes to the
Official MCP Registry as
com.mireye/earth (the entry goes live with the next tagged
release; the publish job ships from release.yml). The registry entry
carries both distributions:
- the PyPI package
mireye-mcp(local stdio, run viauvx), and - the hosted remote
https://api.mireye.com/mcp(Streamable HTTP + OAuth) for clients that prefer a remote server.
Once the entry is live, registry-aware clients (VS Code, the GitHub MCP Registry, and anything else that reads the official registry) can discover and install it from there — no manual config required.
Wire it into Claude Desktop
First authenticate the local adapter:
mireye-mcp login
For non-interactive hosts, set MIREYE_BEARER_TOKEN instead.
Edit ~/Library/Application Support/Claude/claude_desktop_config.json
(macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"mireye-earth": {
"command": "uvx",
"args": ["mireye-mcp"]
}
}
}
Restart Claude Desktop. The two tools (mireye_ask, mireye_fetch)
appear under the 🔌 menu, with catalog resources and prompts available to
clients that surface those MCP primitives.
To point at a self-hosted deployment instead of the default Fly URL:
{
"mcpServers": {
"mireye-earth": {
"command": "uvx",
"args": ["mireye-mcp"],
"env": {
"MIREYE_BASE_URL": "https://your-deploy.example.com"
}
}
}
}
Wire it into Claude Code
Use the hosted HTTP MCP endpoint instead of this local stdio package:
claude mcp remove mireye-earth -s user # only needed if an old stdio entry exists
claude mcp add --transport http --scope user mireye-earth https://api.mireye.com/mcp
Restart Claude Code, run /mcp, and follow the browser OAuth flow.
Slash commands appear as:
/mcp__mireye-earth__mireye_ask <lat> <lng> <question>/mcp__mireye-earth__mireye_fetch <lat> <lng> [fields] [preset]
Or just chat naturally — Claude Code will call the tool when relevant.
Wire it into Cursor
Cursor's MCP config lives at ~/.cursor/mcp.json (global) or
<repo>/.cursor/mcp.json (workspace). Same shape as Claude Desktop:
{
"mcpServers": {
"mireye-earth": {
"command": "uvx",
"args": ["mireye-mcp"]
}
}
}
Open Cursor → Settings → MCP and confirm mireye-earth shows the two
green tools. Catalog resources and prompts appear when the client supports
those MCP primitives.
Wire it into a custom agent
If you're building an MCP client with the mcp Python SDK, point its
StdioServerParameters at the installed entry point:
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
params = StdioServerParameters(command="uvx", args=["mireye-mcp"])
async with stdio_client(params) as (read, write):
async with ClientSession(read, write) as session:
await session.initialize()
tools = await session.list_tools()
# tools.tools is [mireye_ask, mireye_fetch]
resources = await session.list_resources()
prompts = await session.list_prompts()
result = await session.call_tool(
"mireye_ask",
{"lat": 40.7128, "lng": -74.0060, "question": "elevation?"},
)
Configuration
| Env var | Default | Purpose |
|---|---|---|
MIREYE_BASE_URL |
https://api.mireye.com |
HTTP base URL the tools POST to. Stored login credentials only attach when they were created against this same URL. |
MIREYE_TIMEOUT_S |
60 |
Per-request timeout in seconds. |
MIREYE_BEARER_TOKEN |
unset | Optional Mireye bearer token. Overrides stored credentials for tool calls; status reports on the stored login first. |
MIREYE_MCP_CREDENTIALS_FILE |
~/.config/mireye-mcp/credentials.json |
Stored token path used by login / status / logout. |
Authentication
The local stdio adapter does not perform native MCP OAuth discovery.
The HTTP API requires bearer auth for /v1/ask and /v1/fetch, so run
the device login helper once:
mireye-mcp login
The command prints a verification URL and code, waits for approval in the Mireye account page, and stores a Mireye API token locally. You can also provide a token directly:
{
"mcpServers": {
"mireye-earth": {
"command": "uvx",
"args": ["mireye-mcp"],
"env": {
"MIREYE_BEARER_TOKEN": "eyJ..."
}
}
}
}
Check or remove local credentials:
mireye-mcp status
mireye-mcp logout
mireye-mcp logout --revoke
Credentials are bound to their base URL
login records the MIREYE_BASE_URL it ran against, and the stored
token is only ever sent to that same URL. If MIREYE_BASE_URL later
points somewhere else, tool calls behave as logged out and the error
names both URLs — re-run mireye-mcp login against the new URL,
or set MIREYE_BEARER_TOKEN explicitly. Credentials files without a
recorded base_url (e.g. hand-written) are treated as bound to the
default https://api.mireye.com.
Two more guardrails:
- Tokens of any kind are never sent over plain
http://, except to loopback hosts (localhost/127.0.0.1/[::1]) for local development. statusandlogout --revokeoperate on the stored base URL, so you can always inspect or revoke a stored login even whileMIREYE_BASE_URLpoints elsewhere.
For native MCP OAuth, configure your client to use the hosted remote MCP
URL https://api.mireye.com/mcp instead of launching this stdio
binary. The remote endpoint advertises OAuth metadata and uses browser
OAuth 2.1 + PKCE.
Troubleshooting
Server doesn't appear in Claude Desktop. Check that uvx resolves
on the PATH used by the GUI app (macOS launches GUI apps with a minimal
PATH). Test from a terminal: which uvx. If empty, install uv:
curl -LsSf https://astral.sh/uv/install.sh | sh. If uvx lives at
/Users/you/.local/bin/uvx, use the absolute path in command.
Tools not appearing under the 🔌 menu after restart. Watch
~/Library/Logs/Claude/mcp-server-mireye-earth.log. The server logs to
stderr on startup; you should see [mireye-mcp] starting base_url=…. If there's no log, uvx isn't being invoked — usually a
PATH issue.
ConnectError / ReadTimeout on the first tool call. The hosted
API keeps its machines running, but calls right after a backend deploy
can be slow while geospatial sources warm in the background, and some
fields depend on slow upstream federal services. Increase
MIREYE_TIMEOUT_S to 90 if you are repeatedly hitting timeouts.
HTTP 400 coord_out_of_bounds. Mireye is US-only in V1. The accepted
envelope is lat ∈ [18, 72], lng ∈ [-180, -65] — covering the lower 48,
Alaska, Hawaii, and US territories.
HTTP 400 fields_unknown. The field name is not in the catalog. Hit
https://api.mireye.com/v1/meta/fields to see the canonical list.
Common surprises: elevation_m is elevation, floodplain is
within_floodplain_polygon.
HTTP 4xx/5xx in general. Tool errors include actionable JSON fields
such as code, message, http_status, request_id, tool, and
retryable. Agents should retry only when retryable is true.
Auth errors. 401 means the MCP server has no token, the token
expired, or the token was revoked. Run mireye-mcp login again,
or set MIREYE_BEARER_TOKEN. 403 means the signed-in account is not
allowed by the backend account policy.
What this server does NOT do
- No data-result caching. The HTTP API has its own response cache (local disk, plus a shared Redis tier in production). The stdio adapter only caches the public field catalog resource.
- No geospatial business logic. The adapter validates obvious MCP input bounds and field-count limits, but source orchestration stays in the API.
- No streaming. MCP streaming responses are V1.5.
- No Firebase validation in MCP. The MCP package forwards bearer tokens; the HTTP API owns token verification and account policy.
- No in-process imports of
mireye_earth. The server talks to the API over HTTP only, so it ships as a separate slim PyPI package (mireye-mcp) and can be installed without the data backend.
Releasing
This package is published from this directory on every v* tag on the
main repo. To release locally:
cd mcp_server
python -m build
twine upload dist/*
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