# Taco Street Locating (remote · ai.tacostreetlocating.com)

Free human-backed apartment locating for Austin, Dallas & Houston, TX. A free locator books tours.

- Trust score: 78/100 (medium)
- Change this week: +4
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-24

## Components

- remote · `ai.tacostreetlocating.com`: 78/100 (this document), [markdown](https://verifymcp.io/servers/com-tacostreetlocating-ai-taco-street-locating/ai.md), [page](https://verifymcp.io/servers/com-tacostreetlocating-ai-taco-street-locating/ai)

## Channel facts

- Endpoint: `https://ai.tacostreetlocating.com/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.2.2`

## 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 2026-09-24.

- **Endpoint Security**: 77/100
  - 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.
  - HSTS check failed: the Strict-Transport-Security header is absent.
  - DNSSEC is configured correctly; the domain's records validate against the full chain to the root.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 69/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 1744 tokens (~193/item across 9 items; 9 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 57/100
  - Stability observed for 17 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% 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.
  - We read all 9 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 10 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 60/100
  - Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28.

## Install

### How do I install the Taco Street Locating MCP server?

Taco Street Locating is a hosted endpoint at https://ai.tacostreetlocating.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-tacostreetlocating-ai-taco-street-locating 'https://ai.tacostreetlocating.com/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "com-tacostreetlocating-ai-taco-street-locating": {
      "url": "https://ai.tacostreetlocating.com/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "com-tacostreetlocating-ai-taco-street-locating": {
      "type": "http",
      "url": "https://ai.tacostreetlocating.com/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.com-tacostreetlocating-ai-taco-street-locating]
url = "https://ai.tacostreetlocating.com/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "com-tacostreetlocating-ai-taco-street-locating": {
      "type": "remote",
      "url": "https://ai.tacostreetlocating.com/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add com-tacostreetlocating-ai-taco-street-locating --url 'https://ai.tacostreetlocating.com/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  com-tacostreetlocating-ai-taco-street-locating:
    url: "https://ai.tacostreetlocating.com/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "com-tacostreetlocating-ai-taco-street-locating": {
      "Transport": "http",
      "Url": "https://ai.tacostreetlocating.com/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add com-tacostreetlocating-ai-taco-street-locating -t streamable-http -u 'https://ai.tacostreetlocating.com/mcp'
```

### Other

```json
{
  "mcpServers": {
    "com-tacostreetlocating-ai-taco-street-locating": {
      "type": "http",
      "url": "https://ai.tacostreetlocating.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.

### 2026-09-24 (score 78, +1)

No change was recorded against any check on this day. Stability & Change Management went from 53 to 57. That category is still filling its 30-day observation window: 16 days of observed history at the previous scan, 17 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-22 (score 77, +1)

No change was recorded against any check on this day. Stability & Change Management went from 47 to 50. That category is still filling its 30-day observation window: 14 days of observed history at the previous scan, 15 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-20 (score 76, +1)

No change was recorded against any check on this day. Stability & Change Management went from 40 to 43. That category is still filling its 30-day observation window: 12 days of observed history at the previous scan, 13 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-18 (score 75, +1)

No change was recorded against any check on this day. Stability & Change Management went from 33 to 37. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 11 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-16 (score 74, 0)

- [security] The server rewrote its instructions, which are the text every model session reads
- [functional regression] Schema quality: 159 → 193
- [functional] Server version: 1.2.2 → 1.5.0
- [functional] New tool “get_research_request”
- [functional] New tool “request_apartment_research”
- [functional] New tool “request_research_tours”

### 2026-09-14 (score 74, +1)

No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-12 (score 73, +1)

No change was recorded against any check on this day. Stability & Change Management went from 13 to 17. That category is still filling its 30-day observation window: 4 days of observed history at the previous scan, 5 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-10 (score 72, +1)

No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

## MCP tools (9)

### `search_apartments` (~143 tokens)

Search apartments

Search Taco Street's curated apartment inventory in Austin, Dallas or Houston, TX. Returns scored matches with starting prices and a short 'why' per building. Use for long-term rentals only.

Input parameters:

- `bedrooms` (string): Bedroom count the renter needs.
- `budget_max` (integer): Max monthly rent in USD.
- `city` (string, required): Metro to search.
- `limit` (integer): How many scored matches to return (1-10).
- `neighborhoods` (array): Preferred neighborhoods, if the renter named any.
- `query` (string): What the renter wants, in plain language (e.g. 'walkable, dog-friendly, near downtown').

Output parameters:

- `apartments` (array)
- `city` (string)
- `count` (integer)
- `note` (string)

### `request_locator_help` (~221 tokens)

Request a free human locator

Hand the renter to Alexander, Taco Street's human locator, who confirms live pricing/availability and books tours — free to renters (properties pay locators). Follow-up arrives by TEXT or EMAIL, never a cold call. Requires the renter's real phone or email, shared with their consent. One request per renter — duplicates within 24h return the existing lead.

Input parameters:

- `agent` (string): Name of the referring assistant/product.
- `bedrooms` (string): Bedroom count the renter needs, e.g. 1BR.
- `budget_max` (integer): The renter's max monthly rent in USD.
- `city` (string): Metro the renter is searching (Austin, Dallas or Houston).
- `contact` (string, required): The renter's phone number or email (with their consent).
- `move_in` (string): Move-in timeline, e.g. 'November'.
- `name` (string): The renter's name, if shared.
- `neighborhoods` (array): Neighborhoods the renter prefers.
- `note` (string): Anything the locator should know.

Output parameters:

- `duplicate` (boolean)
- `lead_id` (string)
- `message` (string)
- `success` (boolean)

### `get_apartment_details` (~116 tokens)

Get apartment details

Full fact sheet for one building: floorplan-level pricing with as-of dates, move-in costs (admin/application/parking/pet fees), last-known specials (dated — treat as last-known, not current), amenities, walkability, virtual tour. Use the EXACT name from search_apartments. Compute totals yourself from components; a free human locator confirms live numbers.

Input parameters:

- `city` (string): Metro, to disambiguate same-named buildings.
- `name` (string, required): Exact building name from search_apartments.

Output parameters:

- `address` (string)
- `building` (object)
- `city` (string)
- `guidance` (string)
- `lifestyle_tags` (array)
- `move_in_costs` (object)
- `name` (string)
- `neighborhood` (string)
- `pets` (string)
- `pricing` (object)
- `specials` (object)
- `taco_street_take` (string)

### `create_shortlist` (~111 tokens)

Create a shareable shortlist

Turn finalist apartments into a Taco Street link (/my-list?s=...) that opens the renter's saved list with those buildings added — compare, AI Read, and free tour requests live there. Use the EXACT names returned by search_apartments.

Input parameters:

- `agent` (string): Name of the referring assistant/product.
- `apartment_names` (array, required): Exact building names from search_apartments to save to the renter's list.
- `city` (string): Metro, to disambiguate same-named buildings.

Output parameters:

- `apartments` (array)
- `note` (string)
- `unmatched` (array)
- `url` (string)

### `ask_a_locator` (~199 tokens)

Ask a human locator

Ask a question only a human can answer — current specials, real availability, lease flexibility, 'is the pool actually open'. A human locator replies during Central Time business hours, usually within a few hours. STRONGLY include the renter's contact: the answer is texted/emailed to them directly (agent sessions end; polling alone can strand an answer). Returns a question_id for check_answer as a bonus channel. Rate limited; batch related questions into one. Answers are point-in-time facts.

Input parameters:

- `agent` (string): Name of the referring assistant/product.
- `apartments` (array): Buildings the question is about.
- `city` (string): Metro the question concerns.
- `contact` (string): The renter's phone/email — strongly recommended: the answer is texted/emailed to them directly, and polling alone can strand it.
- `question` (string, required): The question for the human locator — specifics beat generalities.

Output parameters:

- `guidance` (string)
- `question_id` (string)
- `status` (string)

### `check_answer` (~36 tokens)

Check for a locator's answer

Poll the answer to an ask_a_locator question by question_id.

Input parameters:

- `question_id` (string, required): The id returned by ask_a_locator.

Output parameters:

- `answer` (string|null)
- `answered_at` (string|null)
- `guidance` (string)
- `note` (string)
- `question` (string)
- `question_id` (string)
- `status` (string)

### `request_apartment_research` (~402 tokens)

Request an apartment research report

Submit a saved shortlist and renter brief to Taco Street with consent. Staff accepts the request before paid research starts; VAs verify gaps, then Alexander adds his judgment. Returns a private continuation link. No immediate report, guaranteed completion time, or tour booking. No email is sent by this tool.

Input parameters:

- `agent` (string): Self-reported referring assistant or product; not a verified partner identity.
- `bedrooms` (integer, required): Bedroom count, 0 for a studio, 1–4 otherwise.
- `budget_basis` (string): base_rent, total_monthly, or unknown when the renter has not specified.
- `budget_flexibility` (string): Defaults to target. Use hard_max only for an explicitly strict ceiling.
- `budget_max` (number, required): Monthly USD budget; specify its basis and flexibility separately.
- `city` (string, required): Supported search market for this shortlist.
- `client_name` (string, required): Renter's name shared with consent.
- `consent` (boolean, required): True only after the renter agrees to share this brief and contact for research and follow-up.
- `contact` (string, required): Renter's email or phone shared with consent for research follow-up.
- `lease_term_months`: Requested lease length if known; omit when unknown.
- `move_in` (string, required): Move-in month YYYY-MM or exact date YYYY-MM-DD. Never invent a day; confirm the year.
- `move_in_flexibility` (string): Whether the move-in date is fixed or flexible.
- `notes` (string): Renter requirements and questions, not assistant-generated promises.
- `request_key` (string, required): Generate a fresh cryptographically random URL-safe key (at least 32 random bytes, 43 encoded characters). Keep it private. Reuse it only to retry this identical request and retrieve its status; a dif…
- `shortlist_token` (string, required): The s parameter from the create_shortlist URL.

Output parameters:

- `apartments` (array)
- `continuation_url` (string)
- `criteria` (object)
- `duplicate` (boolean)
- `guidance` (string)
- `report` (object)
- `request_id` (string)
- `status` (string)

### `get_research_request` (~79 tokens)

Continue apartment research

Use the private request key to retrieve progress and, after Alexander approves, the reviewed report snapshot. No draft, contact details or internal notes are returned. Do not share the key or continuation link publicly.

Input parameters:

- `request_id` (string, required): ID returned by request_apartment_research.
- `request_key` (string, required): The original private request key.

Output parameters:

- `apartments` (array)
- `continuation_url` (string)
- `criteria` (object)
- `duplicate` (boolean)
- `guidance` (string)
- `report` (object)
- `request_id` (string)
- `status` (string)

### `request_research_tours` (~169 tokens)

Request tours from your reviewed research

After report approval and explicit renter consent, request human tour coordination for selected apartments. Include preferred dates, times and timezone in preferred_times. Uses the existing private research key and contact. One handoff per research report; identical retries return the existing request, changed preferences require staff follow-up. No appointment is booked or message sent.

Input parameters:

- `apartment_names` (array, required): Exact apartment names from this report to discuss touring.
- `consent` (boolean, required): True only after the renter explicitly agrees to tour coordination using their saved contact.
- `preferred_times` (string, required): Renter-provided preferred dates, times and timezone; preferences are not confirmed appointments.
- `request_id` (string, required): ID of the approved research request.
- `request_key` (string, required): Original private research access key. Never share publicly.

Output parameters:

- `apartments` (array)
- `continuation_url` (string)
- `criteria` (object)
- `duplicate` (boolean)
- `guidance` (string)
- `report` (object)
- `request_id` (string)
- `status` (string)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/com-tacostreetlocating-ai-taco-street-locating/ai#diagnostics

## Score history

- 2026-09-24: 78
- 2026-09-23: 77
- 2026-09-22: 77
- 2026-09-21: 76
- 2026-09-20: 76
- 2026-09-19: 75
- 2026-09-18: 75
- 2026-09-17: 74
- 2026-09-16: 74
- 2026-09-15: 74
- 2026-09-14: 74
- 2026-09-13: 73
- 2026-09-12: 73
- 2026-09-11: 72
- 2026-09-10: 72
- 2026-09-09: 71
- 2026-09-08: 71
- 2026-09-07: 62

## Common questions

### What is the Taco Street Locating MCP server?

Taco Street Locating is an MCP server listed in the public MCP registry as com.tacostreetlocating.ai/taco-street-locating. Free human-backed apartment locating for Austin, Dallas & Houston, TX. A free locator books tours. This page covers its hosted endpoint (https://ai.tacostreetlocating.com/mcp).

### Is the Taco Street Locating MCP server safe to use?

Taco Street Locating scores 78 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 Taco Street Locating MCP server expose?

Taco Street Locating exposes 9 tools: search_apartments, request_locator_help, get_apartment_details, create_shortlist, ask_a_locator, and 4 more. Their descriptions and schemas cost roughly 1,476 tokens of context every time the server is loaded.

### Does the Taco Street Locating MCP server require authentication?

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

### Is the Taco Street Locating MCP server still maintained?

Taco Street Locating is still listed as active in the MCP registry. We last reached this channel on 24 September 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://ai.tacostreetlocating.com/mcp
- Website: https://ai.tacostreetlocating.com/
- Changelog RSS feed: https://verifymcp.io/servers/com-tacostreetlocating-ai-taco-street-locating/ai.xml
- Changelog JSON feed: https://verifymcp.io/servers/com-tacostreetlocating-ai-taco-street-locating/ai.json
- HTML version of this page: https://verifymcp.io/servers/com-tacostreetlocating-ai-taco-street-locating/ai