Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Deterministic GIS geoprocessing with verifiable provenance on every output
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
MAPSMITH_WORKSPACE필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"mapsmith": {
"command": "uvx",
"args": [
"mapsmith"
],
"env": {
"MAPSMITH_WORKSPACE": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add mapsmith --env MAPSMITH_WORKSPACE=your-value -- uvx mapsmith실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"mapsmith": {
"command": "uvx",
"args": [
"mapsmith"
],
"env": {
"MAPSMITH_WORKSPACE": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"mapsmith": {
"type": "stdio",
"command": "uvx",
"args": [
"mapsmith"
],
"env": {
"MAPSMITH_WORKSPACE": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
MAPSMITH_WORKSPACE env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 mapsmith-ai 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.12.1)은 3일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv), Docker도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, LickityClick
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Create, edit and track LickityClick short links, campaigns and click stats from your AI assistant.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Ask a question about your data. Get an analysis — and the record that proves it.
Most GIS servers hand an agent a tool to run. MapSmith takes the question, works out the *analysis* — usually several operations, in an order that has to be right — validates the plan before a single file is touched, runs it, and leaves a record of every step — which bytes went in, with which parameters and CRS decisions, and which checks ran — that somebody else can read afterwards and rerun to confirm.
Point any MCP client at MapSmith (one JSON block) and ask, in your own words:
Which parcels lie within 1.5 km of the river and sit at 120 m or lower? Give me the mean
elevation and the ground area of each.
That is five operations, two coordinate systems and forty-eight checks. [What actually happens is below](#a-whole-analysis-start-to-finish) — the plan, the step that gets rejected for reading something a later step produces, the CRS decision behind every metric step, and an answer you can work out on paper before MapSmith sees the files. That rejection is structural, and so is every other one: a plan that is well formed and answers the wrong question runs instead, which is measured and written down further down this page.
The operations are executed by GeoPandas, DuckDB Spatial, exactextract and Whitebox Workflows — never by the model that asked for them. Every dataset lands on disk next to a lineage manifest: inputs with checksums, the exact parameters, the CRS decisions and *why*, engine versions, and the deterministic checks that ran on the result.
[mapsmith.dev](https://mapsmith.dev) — a real terrain analysis and the manifest that came with it. Both are build products: the figure is rendered from GeoTIFFs MapSmith writes, so the page cannot drift from what the software does.
The manifest is a specified format, not MapSmith's private output: JSON Schema, a toolchain-free validator, a conformance suite, and a hundred-line emitter that never imports MapSmith. Records carry spec_version, and CI validates real MapSmith output against the spec's own validator. The specification is archived and citable as 10.5281/zenodo.22205213, a concept DOI that resolves to the latest *archived* draft. Records written by 0.8.0 to 0.12.1 declare 1.0.0-draft.10, and 0.7.x's declare 1.0.0-draft.8; if the DOI shows an earlier one, the archive has not caught up, and the repository holds the text they are written against. The names MapSmith puts in a record beyond the ones the specification defines — every extension check name, and every extension field in crs_decisions with the reason it is not a synonym of a key the specification already has — are listed in docs/manifest-vocabulary.md, generated from the source rather than maintained by hand.
Evidence before promises. A correctness suite in its own organisation, Argleton, grades MapSmith on thirty-three traps whose answers are computed on paper before any system runs: 0.00 silent errors, nothing skipped, against 0.8788 for the obvious way of writing the same code. The runs from 2026-08-30 to 2026-09-15 said 0.00 too, and on one trap they were wrong: its truth was wrong in MapSmith's favour for 26 days, the error was ours twice over, and the erratum says so. Every run since 2026-09-26, the current one included, is scored against the corrected truth. Getting here cost seven defects the suite sent back, and they are listed. Alongside it: an A/B on GABench whose headline is a null result — with the analysis that took our own positive number apart — notebooks on a real USGS DEM of Mount St. Helens, an in-chat map panel that shows the verification status of every layer it draws, and a measurement of our own tool discovery that retracted two numbers this page had already published — including the one in the bullet list below.
This is the thing MapSmith is for, and it is not a single tool call. One question — six parcels, a river, an elevation grid — becomes a plan of five operations chosen out of 81, validated before anything runs, executed step by step, and recorded: the search that narrowed the catalogue, the arguments that mattered, the CRS decision behind each metric step, and the checks that ran on every result.
Nothing in this section is drawn. benchmarks/worked_example.py builds fixtures whose answer can be worked out on paper, asks the catalogue in the words of the problem, validates and runs the plan, reads the manifests, and writes what follows; tests/test_worked_example.py fails if this page and that script disagree. The position column is BM25's rather than the default engine's, because a published figure should not depend on whether a model download succeeded on the machine that built the page — the narrowing, which is the point, is identical on both. Two things worth watching: the middle column, where the catalogue goes from 81 operations to a handful the caller can read; and the CRS column, where every metric operation says which coordinate system it moved the data into and why.
flowchart TB
ASK[" Parcels within 1.5 km of the river whose mean ground elevation is at most 120 m, with the elevation and the ground area of each "] ASK --> PLAN{{"plan validated before anything runs"}} PLAN -. "rejected: FORWARD_REFERENCE" .-> BAD["'mask_path' references '$buffer' which runs later — move step 'buffer' before 'near'"] BAD:::bad BUFFER[" buffer_layer 81 operations → 28 candidates → chosen CRS EPSG:32610 9/9 checks"] PLAN --> BUFFER NEAR[" clip_layer 81 operations → 13 candidates → chosen CRS EPSG:4326 12/12 checks"] BUFFER --> NEAR HEIGHT[" zonal_statistics 81 operations → 2 candidates → chosen CRS EPSG:4326 7/7 checks"] NEAR --> HEIGHT AREA[" measure_area 81 operations → 25 candidates → chosen CRS WGS 84 (ellipsoidal) 10/10 checks"] HEIGHT --> AREA FILTER[" select_features 81 operations → 25 candidates → chosen CRS EPSG:4326 10/10 checks"] AREA --> FILTER OUT[["3 parcels, each with elevation and ground area"]] FILTER --> OUT classDef bad stroke-dasharray: 4 3
| what the agent asks for | it declares | candidates | picked | at position |
|---|---|---|---|---|
| “everything within one and a half kilometres of the river” | vector, dataset:vector, 1 dataset(s), line | 28 of 81 | buffer_layer | 2 |
| “keep only the parcels that fall inside that strip” | vector, dataset:vector, 2 dataset(s), polygon | 13 of 81 | clip_layer | 1 |
| “how high is the ground under each of these parcels” | raster, dataset:vector, 2 dataset(s), polygon | 2 of 81 | zonal_statistics | 2 |
| “how big is each one on the ground” | vector, dataset:vector, 1 dataset(s), polygon | 25 of 81 | measure_area | 1 |
| “drop the ones where the ground is above 120 metres” | vector, dataset:vector, 1 dataset(s), polygon | 25 of 81 | select_features | 1 |
| step | operation | arguments that mattered | CRS decision, recorded | checks |
|---|---|---|---|---|
| buffer | buffer_layer | distance_meters=1500 | EPSG:32610 — estimated UTM zone for metric buffering on a geographic CRS | 9/9 |
| near | clip_layer | mask_path=$buffer | EPSG:4326 — the mask is already in the input layer's CRS; nothing was reprojected | 12/12 |
| height | zonal_statistics | zones_path=$near, stats=['mean', 'min'] | EPSG:4326 — zones and raster share the same CRS | 7/7 |
| area | measure_area | input_path=$height, method=geodesic | WGS 84 (ellipsoidal) — ground area computed on the WGS 84 ellipsoid, which is where the coordinates are put first; no map plane is involved, so no projection distortion enters | 10/10 |
| filter | select_features | input_path=$area, by=field_between, field=mean, maximum=120 | EPSG:4326 — no CRS change: selecting rows does not touch coordinates | 10/10 |
Every step is inside the plan, the last one included: select_features took 4 rows and returned 3, with a manifest like every other write. This step used to run outside the plan, because the only operation that could answer it was run_sql — which takes its inputs inside a SQL string, declares zero datasets, and therefore cannot join the plan's dataflow. That boundary is deliberate and has not moved: substituting $step into arbitrary strings would be a grammar in which a planner assembles a path out of text. What changed is that it is no longer the only way to ask.
The answer, which can be worked out on paper before MapSmith sees the files: the parcels are squares of 0.0015° at 46.2°N, so each is about 119 m by 167 m, and the elevation ramps west to east across the fixture.
| name | mean | min | area_m2 |
|---|---|---|---|
| North Field | 104.85 | 104.14 | 19303.33 |
| Mill Meadow | 110.51 | 109.8 | 19303.33 |
| Old Orchard | 117.58 | 116.87 | 19303.33 |
The rejected plan is the honest half. Steps in the wrong order are the dominant failure class in the agent benchmark, so the example includes one and shows what the validator says about it, before any file is touched. It earned that place while this was being written: the first version of the plan passed distance_m where the operation declares distance_meters, and the validator named the argument and listed the three it accepts.
You can step through this on [mapsmith.dev](https://mapsmith.dev/#step-through), one beat at a time, along with a second case that GitHub cannot show as well: a file MapSmith refuses. Both are executed while that page is built. The residue of the second one is here, because it is the half nobody demonstrates.
What it declines to answer. Asked *“How high is the ground at each of these two wells?”* against a GeoTIFF that opens in every viewer:
| describing the file first | |
|---|---|
georeferencing_source | sidecar (.aux.xml) |
georeferencing_sidecar_present | terrain.tif.aux.xml |
georeferencing_internal_would_give | cell 10 x 10 at (500000, 5030000) |
terrain.tif is georeferenced twice and nobody chose: the GeoTIFF's own tags say cell 10 x 10 at (500000, 5030000), and terrain.tif.aux.xml beside it says something else. GDAL prefers the sidecar, which is correct — that is how an override works — but sample_raster_at_points would then report numbers from a file you did not name, and this record could not say which. describe_dataset lists both. To choose, either remove the sidecar or set GDAL_GEOREF_SOURCES=INTERNAL for a run that must use the file's own.
A number would have come back. It would have been read off a grid a hundred
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요