# Close Knit (remote · getcloseknit.com)

London neighbourhoods and homes: crime, schools, prices, rents, commute, green space, sourced.

- Trust score: 74/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-10-23

## Components

- remote · `getcloseknit.com`: 74/100 (this document), [markdown](https://verifymcp.io/servers/com-getcloseknit-close-knit/getcloseknit.md), [page](https://verifymcp.io/servers/com-getcloseknit-close-knit/getcloseknit)

## Channel facts

- Endpoint: `https://getcloseknit.com/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `2.0.1`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-10-23.

- **Endpoint Security**: 80/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 74/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 6365 tokens (~254/item across 25 items; 24 tools + 1 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 3/100
  - Stability observed for 1 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 99/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 97% of tool parameters carry a description.
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - All 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation.
  - An AI judge read all 26 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).
  - Supports UI / widget rendering.

## Install

### How do I install the Close Knit MCP server?

Close Knit is a hosted endpoint at https://getcloseknit.com/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

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

### Cursor

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

### VS Code

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

### Codex

```toml
[mcp_servers.com-getcloseknit-close-knit]
url = "https://getcloseknit.com/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "com-getcloseknit-close-knit": {
      "type": "remote",
      "url": "https://getcloseknit.com/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add com-getcloseknit-close-knit --url 'https://getcloseknit.com/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  com-getcloseknit-close-knit:
    url: "https://getcloseknit.com/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "com-getcloseknit-close-knit": {
      "Transport": "http",
      "Url": "https://getcloseknit.com/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add com-getcloseknit-close-knit -t streamable-http -u 'https://getcloseknit.com/mcp'
```

### Other

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

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-10-23 (score 74, +1)

- [security] The server rewrote its instructions, which are the text every model session reads
- [security] Tool “get_area_metric” rewrote its description, which is the text the model reads
- [security] Tool “get_commute” rewrote its description, which is the text the model reads
- [security] Tool “match_areas” rewrote its description, which is the text the model reads
- [security] Tool “rank_areas_by_metric” rewrote its description, which is the text the model reads
- [functional improvement] Stability: unverified → 0.03
- [cosmetic] “rank_areas_by_metric” added an optional parameter “region”
- [cosmetic] “find_areas” reworded the description of “custom”
- [cosmetic] “find_areas” reworded the description of “ranges”
- [cosmetic] “match_areas” reworded the description of “profile”
- [cosmetic] “match_areas” reworded the description of “top_n”

### 2026-10-22 (score 73)

First indexed and scored.

## MCP tools (24)

### `find_areas` (~814 tokens)

Find areas

Shortlist London neighbourhoods for a household: budget, bedrooms, weighted priorities (crime, station access, price level, official deprivation decile, noise, disorder, energy rating, leasehold share) and optional stations/boroughs to live near. Returns ranked areas with score, factor values, a ballpark price for the bedroom count and budget fit, postcode districts and website links. Pass rejected areas in exclude_area_ids when refining after the user's feedback (LSOA, MSOA or borough ids).

Input parameters:

- `bedrooms` (integer): Bedrooms needed (0 = studio).
- `boroughs` (array): Live in these boroughs (uk:borough:E09…, from search_places). Stations + boroughs ≤ 3.
- `budget_importance` (integer): Where the budget sits in the order (5 = first). Fit 1 up to target_budget, falling to 0 at max_budget.
- `budget_must` (boolean): True = areas whose ballpark is over max_budget are out.
- `custom` (array): The user's own criteria from places on the map ('more cafés than kebab shops', 'near gyms'): a preset_id or a criterion, each scored by its percentile within the area's region (London for a London ar…
- `exclude_area_ids` (array): Areas the user already rejected — LSOA, MSOA or borough geography ids (boroughs and MSOAs expand to their LSOAs) — so they are not suggested again.
- `include_over_budget` (boolean): Keep areas whose typical home looks over budget.
- `liked_area_ids` (array): Areas the user liked: carried into the map link and highlighted there.
- `market` (string): Buying or renting.
- `max_budget` (integer, required): Maximum price in £ (buy) or £ per month (rent).
- `near_stations` (array): Live within walking distance of these stations (e.g. on the user's commute line).
- `only_in_zones` (boolean): With stations/boroughs given: True = only areas inside them (a must Where criterion); False = ranked first in the order, the fit falling with distance outside (zone_soft_metres).
- `places` (array): Where the household goes — work, a gym, a particular school, friends (pinned: latitude/longitude from search_places) or the nearest of a kind (category). Each becomes a criterion; must = hard limit.
- `priorities` (array): What matters, with importance 1-5 (criteria are ranked by importance, then in the order given; the order sets the weights). Translate the user's words: 'safe' → crime, 'near the tube' → station-acces…
- `property_type` (string): House or flat, for the price comparison on the brief page (sales of similar homes).
- `ranges` (array): Any other map layer as a range with soft edges, e.g. gigabit broadband at 90% of homes or more: {layer: 'broadband-gigabit', scale: 'value', min: 90}. Bounds are percentiles within each area's region…
- `target_budget`: Comfortable price; defaults to max less 8% (the site's own rule: £650k max → £600k).
- `top_n` (integer): How many areas to return.
- `zone_soft_metres` (integer): Outside the zones the fit falls to 0 over this distance (when only_in_zones is False).

### `open_shared_search` (~142 tokens)

Open shared search

Open a search the user shared from the Close Knit site (a link with #profile=v1., v2. or v3.): their budget, priorities, places (gym, work, schools…), liked and ruled-out areas and private notes, re-ranked now with the same shortlist as find_areas. Use it when the user pastes such a link or says 'discuss my search'.

Input parameters:

- `link` (string, required): An Close Knit link the user shared (…#profile=v1.…, v2. or v3.), e.g. from 'Discuss with Claude' on the site.
- `top_n` (integer): How many areas to return.

### `find_similar_areas` (~109 tokens)

Find similar areas

Neighbourhoods like one the user liked (crime, deprivation, income, price level and station access percentiles), optionally only cheaper ones: 'like this but cheaper / elsewhere'.

Input parameters:

- `area_id` (string, required): A neighbourhood (LSOA) the user liked.
- `bedrooms`: Adds a ballpark price for this size.
- `cheaper` (boolean): Only areas with a lower £/m² price level.
- `top_n` (integer): How many areas to return.

### `get_area_overview` (~200 tokens)

Get area overview

One neighbourhood in detail for a decision: local market (sales, turnover, leasehold share, £/m² medians, growth), the borough's official UK HPI (hpi: average price by type, 1/5/10-year change vs London: 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), council tax bands and a typical bill (councilTax), the IMD decile (deprivation), a ballpark price for a bedroom count and website links.

Input parameters:

- `area_id` (string, required): Geography id, e.g. uk:lsoa:E01000951.
- `bedrooms`: Adds a ballpark price for this size.

### `assess_listing` (~400 tokens)

Assess listing

Check one listing the user found against local evidence: asking price vs the neighbourhood's recorded £/m² (with floor area or a bedroom-based ballpark), turnover, growth, the borough's official HPI, costs (stamp duty on the asking price, the borough's 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.

Input parameters:

- `asking_price` (integer, required): £ (buy) or the rent in its rent_period (rent).
- `bedrooms`: Bedrooms in the listing.
- `floor_area_sqft`: Floor area in sq ft if the listing states it; converted server-side (1 sq ft = 0.092903 m²).
- `floor_area_sqm`: Floor area in m² if the listing states it.
- `listing_url`: Echoed back for citation only.
- `market` (string): For sale or to rent.
- `postcode` (string, required): Full postcode of the listing, e.g. W5 2NU.
- `property_type`: Property type if the listing states it; used for a same-type comparison.
- `rent_period` (string): The rent's period: month = £ per calendar month, week = £ per week (converted ×52/12 for the comparison).
- `share_percent`: Shared-ownership share for sale, e.g. 25: the asking price is compared as asking_price ÷ share against whole-home prices. Omit when the listing does not state it (the verdict stays unknown).
- `tenure` (string): Tenure if the listing states it; lease questions are hedged ('If leasehold') when unknown and skipped for freehold.

### `list_metrics` (~136 tokens)

List metrics

List every area metric the active release serves (id, unit, direction, available periods, legend, provenance, caveats), plus the My match factors (kind 'factor': disorder, epc-share, leasehold-share, schools) that get_area_metric and rank_areas_by_metric also read. Call first to learn valid metric_id/period values for the other area tools; compact=true returns only id, unit, direction and defaultPeriod. Sources carry licence and methodology links.

Input parameters:

- `compact` (boolean): Only id, unit, direction and defaultPeriod per metric: a small reply when you just need valid metric_id/period values.

### `search_areas` (~109 tokens)

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.

Input parameters:

- `limit` (integer): Maximum results (1-25).
- `q` (string, required): Free text: area name, ONS code (E01…), postcode, or street.

### `get_area_metric` (~267 tokens)

Get area metric

Evidence-backed value of one metric for one area in one month: value, regional (londonPercentile: 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, leasehold-share and schools are read the same way for one neighbourhood (latest value, period ignored), to verify or explain a find_areas result.

Input parameters:

- `area_id` (string, required): Geography id, e.g. uk:lsoa:E01000004.
- `metric_id` (string, required): Metric id from list_metrics, e.g. crime or price-per-square-metre.
- `period`: Month, YYYY-MM. Defaults to the metric's latest period (defaultPeriod in list_metrics).

### `rank_areas_by_metric` (~305 tokens)

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, leasehold-share and schools rank too (latest value, period ignored).

Input parameters:

- `metric_id` (string, required): Metric id from list_metrics.
- `order` (string): desc = highest value first.
- `period` (string, required): Month, YYYY-MM.
- `region`: Only areas of one English region: its code (E12000001-E12000009) or name, e.g. 'North West', 'London'. Omitted: every area Close Knit covers.
- `top_n` (integer): How many areas to return (1-50).

### `get_address_history` (~108 tokens)

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.

Input parameters:

- `address_id` (string, required): Address id returned by search_areas (uk:addr:…).

### `get_home_prices` (~332 tokens)

Get home prices

One London 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 borough), 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.

Input parameters:

- `property_ref` (string, required): UPRN (digits), an address id (uk:addr:…) as returned by search_places, or an address fragment, e.g. '100a Baker Street EN1'.

### `match_areas` (~558 tokens)

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.

Input parameters:

- `profile` (object, required): preference-profile.v2 (preferred): {schemaVersion: 'preference-profile.v2', market buy|rent, targetBudget, maximumBudget, bedrooms, criteria: [...]} where criteria is ORDERED, most important first, e…
- `top_n` (integer): How many of the best-scored areas to list (1-100). values is that top-N list, not the whole map; scored, unscored, excluded and excludedBy count every area Close Knit covers. For the whole map use ma…

### `get_market_depth` (~146 tokens)

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.

Input parameters:

- `area_id` (string, required): LSOA or MSOA geography id, e.g. uk:lsoa:E01000004 (boroughs are unavailable).

### `get_nearby_sales_summary` (~112 tokens)

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.

Input parameters:

- `address_id` (string, required): Address id returned by search_areas (uk:addr:…).

### `get_area_evidence_pack` (~132 tokens)

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, 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.

Input parameters:

- `address_id`: Optional address id (uk:addr:…) inside the area: adds its building and street sale aggregates.
- `area_id` (string, required): Geography id, e.g. uk:lsoa:E01000004.

### `search_places` (~159 tokens)

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, boroughs (uk:borough:…) for find_areas.boroughs, areas and addresses for get_area_overview and assess_listing.

Input parameters:

- `limit` (integer): Results per kind.
- `q` (string, required): A station, borough, neighbourhood, postcode or street.

### `get_commute` (~208 tokens)

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 no minutes (reason 'outside-london', or 'outside-coverage' where Close Knit covers England). Journeys over 120 minutes are not timed (minutes null, capped: true).

Input parameters:

- `area_id` (string, required): The neighbourhood (LSOA) to travel from.
- `places` (array, required): Pinned places (latitude/longitude) to reach.

### `get_flood_risk` (~109 tokens)

Get flood risk

Flood bands for an area's land (rivers/sea, surface water) and, with a UPRN, that home's own bands. Bands show the likelihood for an area, not a specific property: send the user to the Environment Agency check for one address.

Input parameters:

- `area_id` (string, required): Geography id, e.g. uk:lsoa:E01000951.
- `uprn`: A home's UPRN for its own bands; without it, only the area's land bands.

### `get_rent_levels` (~81 tokens)

Get rent levels

Median monthly rent by bedroom count for areas (the figure the site shows). Borough averages per LSOA; empty for a studio or before the rents are loaded.

Input parameters:

- `area_ids` (array, required): Geography ids, e.g. uk:lsoa:E01000951.
- `bedrooms` (integer, required): Bedroom count; the site shows rents per bedroom count.

### `get_listing_search_links` (~139 tokens)

Get listing search links

Pre-filtered searches on Rightmove, Zoopla, OnTheMarket (and OpenRent for rentals) for the postcode districts of shortlisted areas. Links only: open them on the user's behalf to read listings; Close Knit itself never fetches or stores listings.

Input parameters:

- `area_ids` (array, required): LSOA ids from find_areas.
- `market` (string): Buying or renting.
- `max_price` (integer, required): £ (buy) or £ per month (rent).
- `min_bedrooms` (integer): Minimum bedrooms.
- `outcodes_per_area` (integer): Postcode districts per area (busiest first).

### `list_custom_presets` (~188 tokens)

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.

### `evaluate_custom_criterion` (~187 tokens)

Evaluate custom criterion

Evaluate a criterion from places on the map for every London neighbourhood ('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 London percentiles, the legend and a map link that shows it as a layer. Places, never people: religion or who lives there is refused.

Input parameters:

- `area_ids` (array): Also report these areas (LSOA ids from search_places).
- `criterion`: Or the user's own criterion.
- `direction`: Which end the user wants (for the top list and the map link).
- `preset_id`: A ready-made criterion from list_custom_presets.
- `top_n` (integer): How many top and bottom areas to list.

### `build_watch_spec` (~153 tokens)

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.

Input parameters:

- `area_ids` (array, required): LSOA ids to watch.
- `frequency` (string)
- `market` (string)
- `max_price` (integer, required): £ (buy) or £ per month (rent).
- `min_bedrooms` (integer)
- `must_haves` (string): Free-text requirements the agent checks per listing.
- `name` (string, required): Short name, e.g. 'Ealing 2-bed'.

### `send_feedback` (~213 tokens)

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.

Input parameters:

- `client`: The AI client, e.g. 'claude.ai'.
- `kind` (string, required): bug = a tool failed or misbehaved; missing-data / wrong-data = an answer lacked or got a fact wrong; idea = something to add; praise = what worked well.
- `message` (string, required): What happened or what would help, in a few sentences: the product, never the person. No names, contact details, addresses, family or money circumstances.
- `rating`: How useful Close Knit was, 1-5, if the user said.
- `tools` (array): The Close Knit tools it is about, e.g. ['find_areas'].

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/com-getcloseknit-close-knit/getcloseknit#diagnostics

## Score history

- 2026-10-23: 74
- 2026-10-22: 73

## Common questions

### What is the Close Knit MCP server?

Close Knit is an MCP server listed in the public MCP registry as com.getcloseknit/close-knit. London neighbourhoods and homes: crime, schools, prices, rents, commute, green space, sourced. This page covers its hosted endpoint (https://getcloseknit.com/mcp).

### Is the Close Knit MCP server safe to use?

Close Knit scores 74 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the Close Knit MCP server expose?

Close Knit exposes 24 tools: find_areas, open_shared_search, find_similar_areas, get_area_overview, assess_listing, and 19 more. Their descriptions and schemas cost roughly 5,307 tokens of context every time the server is loaded.

### Does the Close Knit MCP server require authentication?

No. We connected to Close Knit without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the Close Knit MCP server still maintained?

Close Knit is still listed as active in the MCP registry. We last reached this channel on 23 October 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://getcloseknit.com/mcp
- Repository: https://github.com/bmsdave/close-knit-mcp
- Changelog RSS feed: https://verifymcp.io/servers/com-getcloseknit-close-knit/getcloseknit.xml
- Changelog JSON feed: https://verifymcp.io/servers/com-getcloseknit-close-knit/getcloseknit.json
- HTML version of this page: https://verifymcp.io/servers/com-getcloseknit-close-knit/getcloseknit