Close Knit

com.getcloseknit由 getcloseknit.com 发布官方发布者v2.0.8更新于 Nov 7, 2026

Neighbourhood and home evidence for England, London in depth: prices, rents, schools, crime, travel.

已验证Streamable HTTP可网页运行位置与生活金融数据与分析

概览

AI 生成的概览

远程 MCP 服务器,为助手提供英格兰(伦敦更详细)社区与住房的证据——房价、租金、犯罪、学校、洪水风险和通勤,帮助用户选择居住地。

可以做什么
  • 按预算、卧室数、地点和加权优先级筛选并排序社区,并找出与某地相似的区域
  • 解析地点、区域和地址,读取指标、百分位、市场深度、租金、洪水等级和历史成交价
  • 估算工作日门到门的公共交通、骑行、驾车和步行通勤时间
  • 用本地证据核对房源要价,并生成预筛选的房产门户搜索或监控方案
  • 按加权指标为学校排名,并评估基于地图地点的自定义标准(如咖啡馆与烤肉店数量对比)
  • 在用户同意后向团队发送反馈
适用场景
适合用户正在英格兰(尤其是伦敦)决定住在哪里或买房时使用:比较社区、核对房源价格、评估通勤时间、学校、犯罪或洪水风险,或把一次搜索变成持续监控新上房源的任务。
运行要求
需要可访问的远程 Streamable HTTP 端点;无需账号、OAuth 或 API 密钥。助手需支持自定义远程 MCP 连接器,部分客户端会按套餐或地区限制自定义连接器。
安装前请注意
工具以查询为主,但 send_feedback 会把消息文本发送给 Close Knit 团队,应先向用户展示并避免包含个人信息。通勤分钟数和部分条件状态可能只是估算,需自行核实。房源链接会打开第三方门户,Close Knit 本身不抓取这些页面。数据随每次发布变化,demo 模式标记的是示例数据。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Close Knit,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/com.getcloseknit%2Fclose-knit/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "close-knit": {
      "type": "http",
      "url": "https://getcloseknit.com/mcp"
    }
  }
}

README

Close Knit MCP server

[Official MCP Registry] [Close Knit MCP server on Glama] [Listed on mcpservers.org]

Close Knit gives AI assistants evidence about neighbourhoods and homes in England, with London in depth, to help people choose where to live. It is a remote MCP server: recorded sale prices, rents, crime, schools, flood risk, commute times, noise and more, from official open data. Every tool answer is an evidence envelope with a value, a confidence, the evidence[] behind it, its sources[] (with licence) and caveats[]. Every neighbourhood and local authority in England is covered; London adds address-level sale history, door-to-door TfL commute times and London-only layers. Ranks and percentiles compare an area with its own region (rankScope names it). It is free, with no account or sign-in. Website: https://getcloseknit.com · Setup for every assistant: https://getcloseknit.com/agents.

https://getcloseknit.com/mcp
  • Transport: Streamable HTTP
  • Authentication: none (no account, no OAuth, no API key)
  • MCP Registry name: com.getcloseknit/close-knit

Tools

GroupToolWhat it does
Home searchfind_areasShortlist neighbourhoods for a household: budget, bedrooms, places they travel to, weighted priorities.
match_areasScore every area against a household's ordered criteria.
find_similar_areasNeighbourhoods like one the user liked, optionally only cheaper ones.
open_shared_searchOpen a search shared from the Close Knit site (a #profile= link).
search_placesResolve a station, borough, neighbourhood, postcode or street the user mentions.
get_commuteDoor-to-door weekday-morning minutes from an area to the user's places (public transport, bike and more).
Areassearch_areasResolve free text (area name, ONS code, postcode, street) to area ids.
get_area_overviewOne neighbourhood in detail: local market, schools, noise, price trend.
get_area_evidence_packOne cited evidence pack for an area: market depth, crime, noise, schools and more.
list_metricsEvery area metric served, with unit, direction, periods and provenance.
get_area_metricOne metric for one area and month, with percentiles within its region and across England.
rank_areas_by_metricRank all areas, or one region's, by one metric and return the top N.
get_flood_riskFlood bands for an area's land and, with a UPRN, for one home.
get_rent_levelsMedian monthly rent by bedroom count.
Homes and pricesget_home_pricesOne home's recorded sales and the range of prices in its area today.
get_address_historyRecorded sale prices for one address (HM Land Registry).
get_nearby_sales_summaryCounts and median £/m² of recorded sales in the same building and street.
get_market_depthLocal market depth: sales in the last 12 months, turnover, leasehold share.
Listingsget_listing_search_linksPre-filtered portal searches for the postcode districts of shortlisted areas.
assess_listingCheck one listing's asking price and facts against local evidence.
build_watch_specTurn a finished search into a watch for new listings.
Your own criterialist_custom_presetsReady-made criteria built from places on OpenStreetMap.
evaluate_custom_criterionEvaluate a criterion such as "more cafés than kebab shops" for every neighbourhood.
Schoolsrank_schoolsRank schools on weighted measures near a point, in one council, one region or England.
list_school_measuresThe school measures rank_schools can rank by.
Feedbacksend_feedbackSend feedback to the Close Knit team, only after the user agrees.

Add Close Knit to your assistant

Claude (claude.ai)

  1. Open Customize > Connectors.
  2. Click + Add, then Add custom connector.
  3. Name: Close Knit. Remote MCP server URL: https://getcloseknit.com/mcp. Click Continue.
  4. Under Authentication, choose no sign in, then click Add.
  5. In a chat, click + at the lower left, choose Connectors and turn Close Knit on.

On Team and Enterprise plans an owner adds it under Organization settings > Connectors. Free plans allow one custom connector.

Claude Code

bash
claude mcp add --transport http close-knit https://getcloseknit.com/mcp

Codex

Add to ~/.codex/config.toml and restart Codex:

toml
[mcp_servers.close_knit]url = "https://getcloseknit.com/mcp"

ChatGPT

  1. Open Plugins at chatgpt.com/plugins.
  2. Select the plus button, then Add custom MCP server.
  3. Name: Close Knit. Under Connection, Server URL: https://getcloseknit.com/mcp.
  4. Authentication: No authentication.
  5. Review the warning, select I understand and want to continue, then Create as a plugin.
  6. Install the plugin, then type @ in the prompt box and select Close Knit.

Custom MCP servers are available on ChatGPT web; which plans and workspaces allow them depends on your account and workspace settings.

Gemini CLI

bash
gemini extensions install https://github.com/bmsdave/close-knit-mcp

This repository is a Gemini CLI extension: gemini-extension.json connects the remote server and GEMINI.md gives the model short guidance. Restart Gemini CLI after installing.

Gemini app

  1. At gemini.google.com, click Settings, then Connected Apps.
  2. Under Custom apps, click Add a custom app.
  3. Enter https://getcloseknit.com/mcp and click Next, then follow the on-screen steps.
  4. In a prompt, type @ and select Close Knit.

Google currently limits custom apps to people aged 18 or over in the US, signed in with a personal Google Account, with Keep Activity on.

Cursor

[Add Close Knit to Cursor]

The same install link in Cursor's own format:

cursor://anysphere.cursor-deeplink/mcp/install?name=close-knit&config=eyJ1cmwiOiJodHRwczovL2dldGNsb3Nla25pdC5jb20vbWNwIn0%3D

Or add it to mcp.json:

json
{  "mcpServers": {    "close-knit": {      "url": "https://getcloseknit.com/mcp"    }  }}

VS Code

[Install in VS Code]

Or run MCP: Add Server from the Command Palette, choose HTTP, and enter https://getcloseknit.com/mcp. In .vscode/mcp.json:

json
{  "servers": {    "close-knit": {      "type": "http",      "url": "https://getcloseknit.com/mcp"    }  }}

Perplexity

  1. Open Plugins in the sidebar (or Customize > Connectors).
  2. Select Add custom, then Connector, then Add MCP connector, and choose Remote.
  3. Name: Close Knit. MCP Server URL: https://getcloseknit.com/mcp.
  4. Authentication: None. Transport: Streamable HTTP.
  5. Tick the acknowledgement box, click Add, then click the connector card to enable it.

Mistral Le Chat

  1. Open the Connectors page.
  2. Click + Add Connector and switch to the Custom MCP Connector tab.
  3. Connector name: closeknit. Server URL: https://getcloseknit.com/mcp.
  4. Click Connect. No authentication is needed.

Adding a connector needs an administrator; on Free, Pro and Student plans the account owner is the administrator.

Grok

  1. Go to grok.com/connectors.
  2. Click New Connector, then select Custom.
  3. Enter https://getcloseknit.com/mcp.

On Business and Enterprise plans a team admin adds connectors first.

Windsurf (Devin Desktop)

In the Cascade panel, open the ... menu, and in the MCPs section click Open MCP config file. Add:

json
{  "mcpServers": {    "close-knit": {      "serverUrl": "https://getcloseknit.com/mcp"    }  }}

Save the file.

Goose

Desktop: open Extensions in the sidebar, click Add custom extension, choose the Streamable HTTP type and enter https://getcloseknit.com/mcp.

CLI: run goose configure, choose Add Extension, then Remote Extension (Streamable HTTP), and enter the URL. For a single session:

bash
goose session --with-streamable-http-extension "https://getcloseknit.com/mcp"

LM Studio

[Add Close Knit to LM Studio]

Or open the Program tab in the right-hand sidebar, click Install > Edit mcp.json, and add:

json
{  "mcpServers": {    "close-knit": {      "url": "https://getcloseknit.com/mcp"    }  }}

Example answers

Answers from the live server, October 2026. Figures change with each data release.

"How much crime is there around Clapham Junction?" search_areas finds the neighbourhood (Wandsworth 012A, SW11) and get_area_metric(crime) answers: 74.4 recorded crimes per 1,000 residents in the 12 months to August 2026, a higher rate than 58% of London's neighbourhoods and 65% of England's; the largest categories are violence and sexual offences and anti-social behaviour. Source: police.uk street crime, Open Government Licence v3.0. Confidence high (observed, not modelled).

"Where in the North West are homes cheapest per square metre?" rank_areas_by_metric with region: "North West" puts three Blackpool neighbourhoods first at £970/m², tied. Confidence medium: they had too few sales of their own, so the figure is their MSOA's (quality: "fallback"). Source: HM Land Registry Price Paid with EPC floor areas.

"Help me find a 2-bed flat to buy in London under £600k, within 30 minutes of King's Cross." search_places resolves King's Cross, find_areas returns a ranked shortlist with each area's standing, what it meets ("4 of 5"), its commute and ballpark price, and an "Open in Close Knit" link to the same search on the map; get_listing_search_links then opens pre-filtered searches on the property portals.

Every tool, with its full input schema, is also listed in the server card: https://getcloseknit.com/.well-known/mcp/server-card.json.

Data and licences

The answers come from official open data, mostly under the Open Government Licence v3.0: HM Land Registry Price Paid Data and UK House Price Index, ONS Census 2021 and other ONS statistics, police.uk street crime, Ofsted and Department for Education school data, Environment Agency flood risk, Defra noise maps, Ofcom broadband coverage, MHCLG deprivation (IMD 2025) and planning data, Ordnance Survey OpenData, Transport for London open data ("Powered by TfL Open Data") and OpenStreetMap (© OpenStreetMap contributors, ODbL 1.0). Each answer lists its own sources and licences in sources[]; keep those attributions when you reuse the data.

The MIT licence in this repository covers the files in this repository only. The data served by the MCP server keeps its own licences.

Privacy

No account and no personal data are needed. send_feedback only sends what you write, and only after you agree.

Licence

MIT

来源:README.md,提交 02bc4e3

工具

27

find_areas

Find areas

Shortlist neighbourhoods in England (London in depth) for a household: budget, bedrooms, weighted priorities (crime, station access, price level, official deprivation decile, noise, disorder, energy rating, leasehold share) and optional stations or local authorities to live near (regions narrows to English regions, e.g. ['london']; with no regions, stations or boroughs all of England is searched). Returns areas in one order (orderedBy): tier (every must met, then unverified), budget band (within, stretch, over, unknown), then standing 0-100 (with property_type every within-budget area first); present them in that order, never by score (mapScore, the map's colour). meets ('4 of 5') and aheadBecause explain it; budgetLabel says the budget in words ('within budget' only for the type's own figure); factor values with a typed fact (quality measured, modelled, estimate or unknown; range; verifyUrl), typicalPrice (the median recent sale), estimatedPrice and budgetFit (with property_type the type's own figure, priceBasis says which; else a ballpark for the bedroom count), postcode districts and website links. A deal-breaker needs must true (a range or place without it only ranks); tier unverified (mustStatus unknown, verified false, tierReasons) marks a must on an estimate, National Rail beside the routed lines or modelled minutes inside the margin: open the factor's fact.verifyUrl or check that journey on the web before calling it met; a must on a coverage gap leaves the area out (gapLeftOut). A ranked criterion an area has no data for (no crime is published for Greater Manchester) counts as half a fit and is named in that area's notScored: say so. Pass rejected areas in exclude_area_ids when refining after the user's feedback (LSOA, MSOA or local authority ids). The first tool for 'where should we live?'; rank_areas_by_metric sorts by one metric only, match_areas scores a ready preference-profile.v2, search_areas only turns names into ids.

输入参数top_ncustomintentmarketplacesrangesregionsbedroomsboroughsmax_budget必填prioritiesbudget_must另有 11 个

find_similar_areas

Find similar areas

Neighbourhoods like one the user liked (crime, deprivation, income, price level and station access percentiles), optionally only cheaper ones (cheaper_by_percent lower £/m², crime no more than 10 points worse) and within max_budget for bedrooms: 'like this but cheaper / elsewhere'.

输入参数top_nintentarea_id必填cheaperbedroomsmax_budgetproperty_typerate_previouscheaper_by_percent

get_area_overview

Get area overview

One neighbourhood in detail for a decision: local market (sales, turnover, leasehold share, £/m² medians, growth), the local authority's official UK HPI (hpi: average price by type, 1/5/10-year change vs its region: quote this for how prices moved), £/m² price trend, crime with its offence mix (topTypes, a busy-centre note), road/rail noise, nearby state schools with their standing Ofsted grade plus independent schools (schools.independent), planning rules (home: conservation, Article 4, listed buildings, broadband), when its homes were built (buildAge), householder planning (planning: home works, the share refused, approval by kind of works in London, the Renovation score), council tax bands and a typical bill (councilTax), the IMD decile (deprivation), typicalPrice (the median sale of the last 12 months, the figure every tool quotes; property_type gives that type's figure, as find_areas prices it), a flood line, a ballpark price for a bedroom count (buy only), the rent first with market='rent', and website links; detail='full' adds every month, school, HPI type and attribution. Comparisons are with the area's region (regionChange, regionPercentile: London's areas among London's); londonChange and londonPercentile are deprecated aliases holding the same values.

输入参数detailintentmarketarea_id必填bedroomsproperty_typerate_previous

assess_listing

Assess listing

Check one listing the user found against local evidence: asking price vs the same home type's recorded £/m² (with floor area or a bedroom-based ballpark) or median price, the LSOA then its MSOA (all types only as indicative-only), typicalPrice, a flood line, turnover, growth, the local authority's official HPI, costs (stamp duty on the asking price, the council tax by band), crime with its offence mix, noise, schools (state and independent counts), planning rules (home: conservation, Article 4, listed buildings), listed buildings recorded at or near the postcode (listedNearby), the IMD decile, and the questions to ask the agent (lease, service charge, EWS1, listing). Not a valuation.

输入参数intentmarkettenurebedroomspostcode必填listing_urlrent_periodasking_price必填property_typerate_previousshare_percentfloor_area_sqm另有 1 个

list_metrics

List metrics

List every area metric the active release serves by theme (id, label, unit), plus the My match factors (theme my-match-factors: disorder, epc-share, leasehold-share) that get_area_metric and rank_areas_by_metric also read. Call first to learn valid metric_id values; detail=[metric ids or themes] returns those in full (periods, defaultPeriod, legend, provenance, caveats); compact=true returns id, unit, direction and defaultPeriod for every metric. Sources carry licence and attribution.

输入参数detailintentcompactrate_previous

search_areas

Search areas

Resolve free text (area name, ONS code, postcode, street) to geography ids (uk:lsoa|msoa|borough:…) and, where recorded sales exist, address ids (uk:addr:…). Use the returned ids with get_area_metric, rank_areas_by_metric, get_address_history. It only looks names up: to shortlist where to live use find_areas, to resolve a household's places (work, a station, a school) for find_areas or get_commute use search_places.

输入参数q必填limitintentrate_previous

get_area_metric

Get area metric

Evidence-backed value of one metric for one area in one month: value, regional (regionPercentile: within the area's region, London for a London area; rankScope names it) and England percentiles, quality, sample size, category breakdown where available, plus up to 12 prior months as evidence rows. Units follow the metric (per 1,000 residents, GBP/m2). Confidence is high only for observed (not modelled) values. Some metrics are published for a wider area (income per MSOA; rent change and mobile coverage per borough): on a smaller area they return the enclosing area's value with quality 'fallback' and carrierGeographyId naming where it came from. Period defaults to the metric's latest. The find_areas factors disorder, epc-share and leasehold-share are read the same way for one neighbourhood (latest value, period ignored), to verify or explain a find_areas result.

输入参数intentperiodarea_id必填metric_id必填rate_previous

rank_areas_by_metric

Rank areas by metric

Rank every served area (or one region's, region='North West') by one metric for one month and return the top N with rank, value, unit and quality. Tied values share a rank (competition ranking); each row carries tiedCount, the number of areas sharing its value. Use it to answer 'which areas have the lowest crime / highest GBP/m2' or 'the least deprived' (deprivation is the official IMD decile, 10 = least deprived: order desc), 'the highest household income' (income, GBP a year) or 'the most social renting' (social-renting, % of households; neutral, never call it better or worse). Areas with suppressed values are excluded. Census layers (census-*, student-share) describe residents and are refused: never rank areas by who lives there. The find_areas factors disorder, epc-share and leasehold-share rank too (latest value, period ignored). One metric only: to weigh several criteria, budget or commute for a household use find_areas.

输入参数ordertop_nintentperiod必填regionmetric_id必填rate_previous

get_address_history

Get address history

Recorded achieved sale prices for one address id (HM Land Registry Price Paid, GBP, with the EPC floor area where matched; no per-sale GBP/m2). These are historic transactions, never valuations or asking prices. listingLinks open the postcode on Rightmove (past listings and their photos), Zoopla and OnTheMarket: links only, Close Knit does not fetch or host listings.

输入参数intentaddress_id必填rate_previous

get_home_prices

Get home prices

One home's recorded sales (date, price, HM Land Registry link) and prices in its area today: the middle half (25th-75th percentile) of same-type standard sales since three years back, each adjusted to the latest month by the local price index, with sample size and the area used (LSOA, else MSOA, else local authority), and the coarse band its last sale fell in that year (top 10%, top quarter, upper middle, lower middle, bottom quarter, bottom 10%) with today's prices of that band in the area. Accepts a UPRN, an address id (uk:addr:…) from search_places, or an address fragment. Area statistics only: never say what the home is worth; describe the area. When a fragment matches several homes the tool returns their candidates instead of picking one: ask which home, or pass its addressId. Homes without a linked UPRN are reached by address id or fragment and carry uprn null. `facts` holds the home's type and tenure (Land Registry) and, where shown, energy-certificate facts (rating, potential rating, certificate date, built form, age band, rooms, floor level); null fields are not shown for this home; `withheld` lists features held back. Below 5 sales of the type nothing is shown. Hidden homes are not found.

输入参数intentproperty_ref必填rate_previous

match_areas

Match areas

Score every area against a household's ordered criteria (preference-profile.v2: budget, ranges on any map layer, places, where zones, own criteria; must = filter). Returns a match-pack.v2 with the best top_n (default 20, max 100) areas as a list with score, rank and percentile per area, its top 2 reasons and 2 weakest criteria, the bottom 10, and per-criterion components (value, fit, in/edge/out) as evidence for the listed areas only. Whole-coverage counts (scored, unscored, excluded, and excludedBy per unmet must) cover every area; mapUrl opens the full map for the search. Set analyticsConsent true only if the user agreed to store an anonymised profile summary; the tool works identically with false. Takes a ready profile (built by you or exported from the site); for a conversational home search use find_areas, which builds the profile from plain answers and adds ballpark prices.

输入参数top_nintentprofile必填rate_previous

get_market_depth

Get market depth

Local market depth of one LSOA or MSOA from HM Land Registry Price Paid (standard category A sales only): sales in the last 12 months, turnover (% of EPC-linked homes that sold), the leasehold share OF SALES (not of homes), new-build and resale median GBP/m2 over 36 months with the new-build premium (each median needs 10 sales, the premium both), and the LSOA's GBP/m2 growth. Aggregates only: never a valuation, a listing or addresses.

输入参数intentarea_id必填rate_previous

get_nearby_sales_summary

Get nearby sales summary

Counts and median GBP/m2 of other homes' recorded sales in the same building (postcode, house number or name, street) and on the same street (other buildings) as one address id, last 10 years. The median is withheld under 5 standard sales with an EPC floor area. Summary only: no sale rows and no addresses; homes with a privacy objection are left out.

输入参数intentaddress_id必填rate_previous

get_area_evidence_pack

Get area evidence pack

One cited evidence pack for an area: market depth (as get_market_depth), the latest recorded crime rate, road and rail noise shares, state schools within 1.5 km with their standing Ofsted grade, when its homes were built (buildAge), householder planning (planning: home works, the share refused, approval by kind of works in London and the Renovation score) and, given an address_id inside the area, its building and street sale aggregates. Every block names its source release; not advice and not a valuation.

输入参数intentarea_id必填address_idrate_previous

search_places

Search places

Resolve a place the user mentions (station, borough, neighbourhood, postcode, street) to ids. Station lookup forgives spelling (Kings Cross, St James Park, Elephant and Castle) and knows London codes and nicknames (KX, TCR, LST, E&C, ally pally). Returns stations (osm:…, with TfL modes, lines and zone; twin stations such as Hammersmith are listed apart) for find_areas.near_stations, local authorities (uk:lad:…; London's boroughs) for find_areas.boroughs, areas (with ladId) and addresses for get_area_overview and assess_listing, and venues (a pool, gym or sports centre by name, with latitude/longitude to pin as a place). best is the likeliest meaning: a venue named exactly so, then a town, city or council named exactly so above a stop that only shares the name; 'Liverpool St' is the station. A street found only outside the town typed gives best null, reason town-mismatch and candidates with their towns: ask which. query is an alias of q.

输入参数qlimitqueryintentrate_previous

get_commute

Get commute

Door-to-door minutes from one neighbourhood to the user's places on a weekday morning, by public transport (R5 on TfL timetables), bike (at the speed Santander Cycles riders reach; checked against TfL), car (typical morning traffic, no parking) and walking, each with a range. Places within 1.5 km of a commute hub (King's Cross, Bank, Canary Wharf, Oxford Circus…) are routed through it; others in Greater London get a straight-line estimate (estimate: true); places outside Greater London, and every place from a neighbourhood outside London (the routing is London only), get straight-line estimates in every mode, long trips at a main-line speed (estimate: true, reason 'outside-routing'). A neighbourhood served by National Rail only also gets a rail estimate (modes.rail, estimate: true). Example routes start at the neighbourhood's MSOA centre (origin); one far from the headline minutes is representative: false and lists its lines only. Journeys over 120 minutes are not timed (minutes null, capped: true). A place takes latitude/longitude or center [longitude, latitude] from search_places; quote estimate minutes as estimates. Each mode's confidence: 'timetable' (TfL), 'routed' (London streets) or 'approximate' (straight-line estimates). googleMapsUrl opens Google Maps' own route for the user to check: its time, leaving now, not ours.

输入参数intentplaces必填area_id必填rate_previous

get_flood_risk

Get flood risk

Flood bands for an area's land (rivers/sea, surface water) and, with a UPRN, that home's own bands: highestBand (covers ≥1% of the land), highestMappedBand (any land), atRiskShare. Bands show the likelihood for an area, not a specific property: send the user to checkUrl (GOV.UK) for one address.

输入参数uprnintentarea_id必填postcoderate_previous

get_rent_levels

Get rent levels

Average monthly private rent of the local authority by bedroom count for areas (averageMonthlyRent, the figure the site shows; carrier lad: every LSOA of a local authority reads the same). Empty for a studio or before the rents are loaded.

输入参数intentarea_ids必填bedrooms必填rate_previous

list_custom_presets

List custom presets

Ready-made custom criteria built from places on OpenStreetMap, with neutral descriptive names: kebab shops vs cafés, specialty coffee vs kebab shops, sandwich chains vs bakery chains, independent vs chain cafés, the nearest gym or sports centre, bars, pubs and clubs (more or fewer, per 1,000 residents), cinemas, theatres, museums and galleries, universities, the nearest playground or nursery, variety of cuisines, bakeries vs betting shops, takeaways, coworking, bike parking, the nearest EV charging point, the nearest market, the nearest dog park, vet or pet shop. Each has an id for evaluate_custom_criterion and find_areas(custom=[…]), a mapUrl (the map coloured by it) and a one-line definition. Use the names as given: no brand names or value words ('good', 'cheap') in what you tell the user.

输入参数intentrate_previous

evaluate_custom_criterion

Evaluate custom criterion

Evaluate a criterion from places on the map for every neighbourhood in England (London in depth) ('where are more cafés than kebab shops', 'most gyms in the area'), counting the places inside each neighbourhood's boundary: a preset_id or the user's own criterion (sets of OSM tag matchers and a formula). Returns the best and worst areas with place counts and percentiles within each area's region, the legend and a map link that shows it as a layer. Places, never people: religion or who lives there is refused.

输入参数top_nintentarea_idscriteriondirectionpreset_idrate_previous

build_watch_spec

Build watch spec

Turn a finished search into a watch: portal searches per postcode district, filters, a state file path for de-duplication and a ready prompt for a scheduled task in the user's Claude that reports only new listings. Stateless: nothing is stored on Close Knit.

输入参数name必填intentmarketarea_ids必填frequencymax_price必填must_havesmin_bedroomsproperty_typerate_previous

send_feedback

Send feedback

Send feedback about Close Knit to the team: a bug, missing or wrong data, an idea, or what worked. Call it only after the user agrees: show them the message first. Describe the product and what happened, never the person: no names, contact details, addresses, family, budget or other personal circumstances.

输入参数kind必填toolsclientratingmessage必填

rank_schools

Rank schools

Rank schools against the user's weighted criteria (1-8: any school measure from list_school_measures, weight 1-5, higher or lower is better, optional must range) within a pool (near a point, one council, one region, or England) and the map's Schools filter (phase, Ofsted, type, intake, faith). Returns each school's score (weighted mean of its percentiles in the pool), rank and per-criterion value with year and source; a missing value is listed, never a zero. With area_id (an LSOA from find_areas) each school also carries straight-line metres from that neighbourhood. Independent schools are a separate unranked list. Pupil-mix measures score nothing while CLOSE_KNIT_SCHOOL_PUPIL_MIX_RANKED is off. A ranking never promises a school place.

输入参数latlngpoollimitphasefilterintentregionarea_idcouncilcriteria必填radius_km另有 2 个

list_school_measures

List school measures

The rankable school measures for rank_schools: id, label, unit, default direction, and whether it is a pupil-mix measure that cannot be ranked now.

输入参数intentrate_previous

rate_answer

Rate answer

Rate a Close Knit answer by its callId (none: the last answer): rating 1-5, what was good, what was bad or missing, the fix you would want. Use it for the last answer in a conversation; earlier ones go in the next call's rate_previous. It describes the answer, never the user.

输入参数badfixgoodrating必填call_id

版本历史

4
  1. v2.0.8最新Oct 31, 2026
  2. v2.0.7Oct 30, 2026
  3. v2.0.4Oct 29, 2026
  4. v2.0.1Oct 22, 2026

评分

已满足适用检查项的 100%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

  • 近 30 天内可连通必需25 分
  • 已声明认证方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分