SafeStreets
Walkability and pedestrian safety for any US address: scores, neighborhoods, deadly roads.
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质量与安全性
基于对工具定义和协议合规性的自动分析。
上下文开销
这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。
安装
一键安装
将以下内容添加到你的 `claude_desktop_config.json` 文件中:
{
"mcpServers": {
"safestreets": {
"url": "https://safestreets.streetsandcommons.com/mcp"
}
}
}远程端点
https://safestreets.streetsandcommons.com/mcpstreamable-http它能做什么
工具清单
工具(8)
🟢get_walkability_score(address, lat, lon)
Score a US location on how good and how safe it is to walk, from a street address or from latitude/longitude. Call this when someone asks whether a place is walkable, how safe it is to walk, whether they could live somewhere without a car, how a neighborhood compares to another on foot, or when evaluating a specific address or property for walkability or pedestrian risk. The server geocodes an address itself. Coordinates estimated from memory can land on a different place, which then gets a confident score of its own. When an address is given, the reply carries resolvedFrom with the address that was matched. Returns a JSON object: overallScore 0-100 composite displayScore the same score as 0-10, which is how SafeStreets presents it grade A to F tier plain label, e.g. "Very walkable", "Car-dependent" confidence 0-100, how much underlying data was available for this point reportUrl the full SafeStreets report for this point: map, metrics, PDF dataSources the sources that fed this specific result components four scored sub-dimensions, each with a 0-100 score and the individual metrics behind it: dailyReach errands reachable on foot streetSafety street design and pedestrian crash risk transitReach usable transit access walkingComfort shade, heat, air quality, surface plus networkDesign, which carries its metrics (network density, intersection density, block length, dead-end ratio) but reports score 0 at weight 0, so it does not contribute to the composite. Read its metrics, not its score. The keys safety, environmentalComfort and densityContext are backward-compatibility aliases of streetSafety, walkingComfort and dailyReach. They duplicate those objects rather than adding signal. The per-component metrics are the point: you can re-weight or rebuild the composite yourself instead of trusting one number. Coverage and limits: United States only. Pedestrian crash inputs are county-level, so two nearby points can share crash figures. Where the underlying crash record is missing, the safety component is reported as unavailable rather than guessed, and confidence drops accordingly. This does not return driving directions, transit timetables, crime statistics, or property listings.
输入模式
{
"type": "object",
"properties": {
"address": {
"description": "A US street address, intersection or place name, e.g. \"1200 W Foster Ave, Chicago\". Give this or lat/lon. The server geocodes it, so it is the reliable input when exact coordinates are not known.",
"type": "string"
},
"lat": {
"description": "Latitude in decimal degrees, WGS84. US locations only. Required unless address is given.",
"type": "number",
"minimum": -90,
"maximum": 90
},
"lon": {
"description": "Longitude in decimal degrees, WGS84. Negative for the US. Required unless address is given.",
"type": "number",
"minimum": -180,
"maximum": 180
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢compare_locations(locations)
Score 2 to 10 US locations and say how they differ. Use this for "which of these is the most walkable", choosing between addresses, or any question that puts places side by side. Give addresses or coordinates, and a label for each if you want the results matched back to your own names. Returns every location ranked, the best and worst, the spread between them, and the gap on each component. The per-component gap is usually the answer: two places can reach the same composite for opposite reasons, one with errands close by and dangerous streets, the other the reverse. A location that cannot be resolved is reported in errors and the rest are still scored. Each location counts as one call against your allowance.
输入模式
{
"type": "object",
"properties": {
"locations": {
"minItems": 1,
"maxItems": 10,
"type": "array",
"items": {
"type": "object",
"properties": {
"address": {
"description": "A US address. Give this or lat/lon.",
"type": "string"
},
"lat": {
"type": "number",
"minimum": -90,
"maximum": 90
},
"lon": {
"type": "number",
"minimum": -180,
"maximum": 180
},
"label": {
"description": "Your name for this location, echoed back so you can match results to inputs.",
"type": "string"
}
}
},
"description": "The places to compare."
}
},
"required": [
"locations"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢score_many(locations)
Score up to 10 US locations in one request. Use this for a list: properties, branches, listings, sites. Each location counts as one call against your allowance, so a list of ten costs ten. A location that cannot be resolved is reported in errors rather than failing the request.
输入模式
{
"type": "object",
"properties": {
"locations": {
"minItems": 1,
"maxItems": 10,
"type": "array",
"items": {
"type": "object",
"properties": {
"address": {
"description": "A US address. Give this or lat/lon.",
"type": "string"
},
"lat": {
"type": "number",
"minimum": -90,
"maximum": 90
},
"lon": {
"type": "number",
"minimum": -180,
"maximum": 180
},
"label": {
"description": "Your name for this location, echoed back so you can match results to inputs.",
"type": "string"
}
}
},
"description": "The places to score."
}
},
"required": [
"locations"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢get_city_walkability(city)
Walkability score for a whole US city, precomputed. Instant, no analysis. Use this for "how walkable is Houston" rather than scoring a point inside it. Returns the 0-100 composite, the same score as 0-10, the tier, and the four components. Covers 203 cities; a city not in the set returns null, which means not covered rather than not walkable.
输入模式
{
"type": "object",
"properties": {
"city": {
"type": "string",
"description": "City name or slug, e.g. \"Houston\", \"fort worth\", \"chicago\"."
}
},
"required": [
"city"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢find_walkable_neighborhoods(city, limit)
Neighborhoods inside a US city, ranked most walkable first, precomputed. Use this for "which part of Chicago should I live in without a car". Returns up to 25 neighborhoods, each with its 0-10 score, tier and components. Covers 749 neighborhoods across the cities analysed so far, so an empty list means that city has not been broken down yet, not that it has no walkable areas.
输入模式
{
"type": "object",
"properties": {
"city": {
"type": "string",
"description": "City name or slug, e.g. \"Chicago\"."
},
"limit": {
"description": "How many to return, default 25.",
"type": "integer",
"minimum": 1,
"maximum": 25
}
},
"required": [
"city"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢search_neighborhoods(county, metro, state, budget_max, walk_min, ...)
Ranked neighborhood search across every US neighborhood (202,000+), for "where should I move" questions. Use this when someone is relocating and has not picked a town yet: filter to a county set, a metro, a state, a home-price ceiling or a walkability floor, then rank by walkability, transit, zero-car share, demand or home value. Each row carries median home value, median income, price-to-income ratio, commute mode shares, zero-car household share, and where available year-over-year home value growth and property tax rate — so walkability can be read alongside what living there costs. Counties are addressed by 5-digit state+county FIPS codes because county names repeat across states (there are Delaware Counties in PA, OH, NY and IN). Example: Chester PA 42029, Delaware PA 42045, Montgomery PA 42091, New Castle DE 10003. walkabilityIndex is the EPA National Walkability Index on its 1-20 scale, with a national percentile beside it, and sort_by "walk" ranks on it. It is a different scale from the 0-100 SafeStreets score, which comes from scoring one address.
输入模式
{
"type": "object",
"properties": {
"county": {
"description": "Comma-separated 5-digit state+county FIPS codes, e.g. \"42029,42045,42091,10003\". The precise way to scope a county set.",
"type": "string"
},
"metro": {
"description": "Metro name substring, e.g. \"Philadelphia\". Give any of county, metro or state.",
"type": "string"
},
"state": {
"description": "Two-letter state code, e.g. \"PA\".",
"type": "string"
},
"budget_max": {
"description": "Maximum median home value in USD; neighborhoods above it are dropped.",
"type": "number"
},
"walk_min": {
"description": "Minimum EPA walkability index (1-20 scale).",
"type": "number"
},
"transit_min": {
"description": "Minimum transit percentile (0-100).",
"type": "number"
},
"sort_by": {
"description": "Ranking field, default \"demand\".",
"type": "string",
"enum": [
"demand",
"walk",
"home",
"transit",
"zero_car",
"afford",
"wfh",
"pi_ratio"
]
},
"sort_dir": {
"description": "Default \"desc\".",
"type": "string",
"enum": [
"asc",
"desc"
]
},
"limit": {
"description": "Rows to return, default 25, max 100.",
"type": "integer",
"minimum": 1,
"maximum": 100
},
"offset": {
"description": "Pagination offset.",
"type": "integer",
"minimum": 0,
"maximum": 9007199254740991
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢get_dangerous_corridors(city, lat, lon, radiusKm, limit)
Road corridors where pedestrians were actually killed, from federal crash records. Source: NHTSA FARS 2022-2024 (PER_TYP=5, INJ_SEV in 4,6). Each corridor carries the road name, the city, the total pedestrian deaths and a per-year breakdown, so a claim can be checked rather than taken on trust. Give either a city, or a lat/lon with an optional radius. Use this when someone asks which roads are dangerous, where crashes happen, or wants evidence for a specific street. These are recorded deaths, not a model or a prediction: a road absent from the list had no recorded pedestrian fatality in the period, which is not the same as being safe.
输入模式
{
"type": "object",
"properties": {
"city": {
"description": "City name or slug. Give this or lat/lon.",
"type": "string"
},
"lat": {
"description": "Latitude, to search around a point.",
"type": "number",
"minimum": -90,
"maximum": 90
},
"lon": {
"description": "Longitude, to search around a point.",
"type": "number",
"minimum": -180,
"maximum": 180
},
"radiusKm": {
"description": "Search radius in km around lat/lon, default 10.",
"type": "number",
"minimum": 0.1,
"maximum": 50
},
"limit": {
"description": "How many to return, default 25.",
"type": "integer",
"minimum": 1,
"maximum": 25
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢search_insights(query, limit)
Search SafeStreets' published research on walkability, street design and pedestrian safety. Returns the article title, summary, URL and its published questions and answers, so a finding can be quoted and linked rather than paraphrased from memory. 32 articles, each built on named public sources. Use this when someone asks what the evidence says, wants a figure they can cite, or asks a general question about walkability that is not about one specific location.
输入模式
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "What to look for, e.g. \"car free cities\", \"arterial roads\", \"kids walking to school\"."
},
"limit": {
"description": "How many articles, default 5.",
"type": "integer",
"minimum": 1,
"maximum": 10
}
},
"required": [
"query"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}社区
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