Hostaway MCP
This is a read-only MCP server for Hostaway that enables AI agents to query hospitality data — guest conversations, reservations, and listings — without manual API calls. It does not support sending messages or modifying any data.
list_unread_guest_threads– List recent guest threads with unread status and attention signals (e.g., whether a guest needs a reply).get_conversation_context– Fetch a detailed summary of a conversation including guest info, listing details, reservation status, attention signals, and recent message history.get_reservation_brief– Get key reservation details: guest name/email, listing, channel, stay dates, booking status, and occupancy breakdown (adults, children, infants, pets).get_listing_brief– Retrieve core listing info: name, location, capacity, bedrooms, and bathrooms.search_reservations– Look up reservations by guest name, email, listing ID, reservation ID, or arrival/departure date ranges (up to 100 results).search_conversations– Find conversations by guest name, listing ID, reservation ID, or conversation ID (up to 100 results).
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Hostaway MCPshow me the latest unread guest messages"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
hostaway-mcp
Read-only, hospitality-shaped MCP server for Hostaway.
This repo owns the operator product only: local/npm stdio, six read-only
tools, no Cloudflare Worker, and no Seascape booking surface.
V1 Goal
Make Codex and Claude useful in real Hostaway workflows without hand-wiring raw API calls every time.
V1 is intentionally narrow:
read-only only
hospitality-native tools, not raw endpoint parity
optimized for conversation context, reservation lookup, and listing lookup
Related MCP server: guesty-mcp-server
Exact V1 Surface
list_unread_guest_threadsget_conversation_contextget_reservation_briefget_listing_briefsearch_reservationssearch_conversations
Local Development
npm install
npm test
npm run check
npm run buildRun the stdio server locally:
HOSTAWAY_API_TOKEN=your-token-here node dist/cli.jsCreate a local npm package tarball:
npm packAfter publish, run without cloning:
npx hostaway-mcpMCP Client Wiring
For local MCP clients, provide HOSTAWAY_API_TOKEN through the environment and
spawn the published npm package over stdio.
The snippets below are pinned to the current published version:
hostaway-mcp@0.2.0Update that version intentionally when you upgrade.
Claude Desktop (macOS)
Edit ~/Library/Application Support/Claude/claude_desktop_config.json.
If you already have top-level keys like preferences, keep them and add
mcpServers alongside them:
{
"mcpServers": {
"hostaway": {
"command": "npx",
"args": ["-y", "hostaway-mcp@0.2.0"],
"env": {
"HOSTAWAY_API_TOKEN": "your-token-here"
}
}
}
}Restart Claude Desktop after saving the file.
Codex
Edit ~/.codex/config.toml and add:
[mcp_servers.hostaway]
command = "npx"
args = ["-y", "hostaway-mcp@0.2.0"]
[mcp_servers.hostaway.env]
HOSTAWAY_API_TOKEN = "your-token-here"Verify the server is registered:
codex mcp listLocal Built CLI
If you want to run the repo checkout instead of npm, point the client at the built CLI directly:
{
"command": "node",
"args": ["/absolute/path/to/hostaway-mcp/dist/cli.js"],
"env": {
"HOSTAWAY_API_TOKEN": "your-token-here"
}
}Environment Variables
Variable | Required | Default | Description |
| Yes | — | Hostaway API token used to authenticate all requests. |
| No | Hostaway production URL | Override the API base URL (useful for testing). |
V1 Non-Goals
sending guest messages
mutating reservations or listings
Cloudflare Worker transport
Seascape booking/distribution flows
webhook ingestion
background sync pipelines
dashboards or owner reporting
generic REST-to-MCP proxy coverage
Source Design
Available Tools
6 toolsget_conversation_contextC
Return an agent-friendly conversation summary plus recent message history.
| Name | Required | Description | Default |
|---|---|---|---|
| conversationId | Yes | ||
| detailLevel | No | ||
| messageLimit | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| raw | No | |
| guest | Yes | |
| notes | Yes | |
| channel | Yes | |
| listing | Yes | |
| missing | Yes | |
| preview | Yes | |
| attention | Yes | |
| listingId | Yes | |
| reservation | Yes | |
| latestSpeaker | Yes | |
| reservationId | Yes | |
| conversationId | Yes | |
| hasAttachments | Yes | |
| recentMessages | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only hints at formatting ('agent-friendly') without explaining what that means structurally. Doesn't disclose if this is read-only, cached, or rate-limited, and fails to leverage the existing output schema to describe return value structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence of nine words that front-loads the essential value proposition. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema and three parameters with zero schema documentation, the description provides minimal context. It doesn't describe the return structure, explain what constitutes 'recent' history, or clarify the 'agent-friendly' formatting.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, yet the description only loosely alludes to parameters ('recent' hints at messageLimit, 'summary' hints at detailLevel) without explaining constraints, enum meanings (compact vs. full), or the conversationId format requirements.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a conversation summary and message history, specifying the resource (conversation) and output format (agent-friendly). However, it doesn't explicitly differentiate from sibling 'search_conversations' regarding when to use retrieval vs. search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool versus 'search_conversations' or 'list_unread_guest_threads'. No prerequisites mentioned for the required conversationId parameter.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_listing_briefC
Return the minimum useful listing context tied to conversations or reservations.
| Name | Required | Description | Default |
|---|---|---|---|
| listingId | Yes | ||
| detailLevel | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| raw | No | |
| city | Yes | |
| notes | Yes | |
| country | Yes | |
| missing | Yes | |
| bedrooms | Yes | |
| bathrooms | Yes | |
| listingId | Yes | |
| listingName | Yes | |
| personCapacity | Yes | |
| channelFacingName | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It hints at behavior through 'minimum useful' (suggesting lightweight/summary data), but omits critical operational details like caching, auth requirements, or what happens if the listingId doesn't exist. The mention of 'minimum' is the only behavioral cue beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 10 words, front-loaded with no filler. While appropriately concise for the sentence structure, the extreme brevity is inadequate given the complete lack of schema documentation for the two parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 0% schema coverage and no annotations, the description is insufficient. It omits parameter semantics, doesn't clarify the output structure despite having an output schema (which reduces the burden slightly), and lacks usage guidance. A 'brief' tool with enum options needs more context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%—neither 'listingId' nor 'detailLevel' have descriptions. The description fails to compensate by not mentioning parameters at all. It doesn't explain the 'compact' vs 'full' enum values, the expected format for listingId, or that listingId is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Return') and resource ('listing context'), and distinguishes itself from sibling tools like 'get_conversation_context' by clarifying this retrieves context 'tied to conversations or reservations.' However, 'minimum useful' is vague and doesn't specify what data fields are included.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this versus 'get_reservation_brief' or 'get_conversation_context'. It implies usage through the 'tied to' phrasing but lacks explicit when-to-use criteria or guidance on choosing between 'compact' and 'full' detail levels.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_reservation_briefC
Return the minimum useful reservation context for an agent or operator.
| Name | Required | Description | Default |
|---|---|---|---|
| reservationId | Yes | ||
| detailLevel | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| raw | No | |
| notes | Yes | |
| status | Yes | |
| channel | Yes | |
| missing | Yes | |
| guestName | Yes | |
| listingId | Yes | |
| occupancy | Yes | |
| guestEmail | Yes | |
| arrivalDate | Yes | |
| listingName | Yes | |
| departureDate | Yes | |
| reservationId | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It hints at behavioral scope with 'minimum useful' suggesting limited data retrieval, but fails to explain what 'brief' entails, error handling for invalid reservation IDs, or how the detailLevel parameter interacts with the 'minimum useful' concept.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The single sentence is front-loaded with the verb and contains no redundancy. However, extreme brevity becomes a liability given the lack of schema documentation and annotations; the description prioritizes brevity over necessary instructional content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 0% schema coverage and no annotations, the description is insufficiently complete. While an output schema exists (reducing the need to describe returns), the description should explain parameter semantics, especially the detailLevel enum values and reservationId format, which are completely undocumented elsewhere.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% with no descriptions on reservationId or detailLevel. The description completely fails to compensate for this gap—it does not mention that reservationId accepts string or number, nor explain what 'compact' vs 'full' means in the detailLevel enum. Critical parameter semantics are missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'minimum useful reservation context' with specific agent/operator audience, establishing verb (Return), resource (reservation context), and scope (minimum useful). However, it does not explicitly differentiate from sibling 'search_reservations' or explain why to use this over 'get_conversation_context'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool versus alternatives. Given siblings include search_reservations and get_conversation_context, the description should specify this retrieves a specific reservation by ID rather than searching, and provides brief context rather than conversation history.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_unread_guest_threadsB
List recent guest threads with raw unread metadata and derived attention signals.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| messageLimit | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| total | Yes | |
| threads | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It adds valuable context about return content ('raw unread metadata' and 'derived attention signals') but fails to disclose safety properties (read-only status), rate limits, or pagination behavior expected for a listing operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. Every clause earns its place: 'recent' implies time-sensitivity, 'raw unread metadata' specifies data type, and 'derived attention signals' indicates computed value-add beyond basic listing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description appropriately avoids detailing return structures. However, with zero schema descriptions and no annotations, the tool lacks complete documentation for its two optional parameters. Adequate but clear gaps remain for a 2-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, requiring the description to compensate. While 'recent' loosely implies limiting behavior related to the 'limit' parameter, the description completely omits explanation of both 'limit' and 'messageLimit' parameters and their interaction (e.g., whether messageLimit controls preview depth).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description provides a specific verb ('List') and resource ('guest threads'), clearly distinguishing from siblings like search_conversations or get_reservation_brief by focusing on 'guest' and 'unread' scope. It loses one point for not clarifying what 'attention signals' specifically represent (e.g., priority scoring).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like search_conversations or get_conversation_context. It does not indicate prerequisites (e.g., authentication) or when this unread-focused listing is preferable to general searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_conversationsC
Lookup conversations by guest name, listing, reservation id, or conversation id.
| Name | Required | Description | Default |
|---|---|---|---|
| conversationId | No | ||
| reservationId | No | ||
| guestName | No | ||
| listingId | No | ||
| limit | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| total | Yes | |
| results | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but fails to disclose behavioral traits. It doesn't mention the read-only nature, pagination behavior with the 'limit' parameter, what happens when no filters are provided, or result sorting order.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The single sentence is front-loaded with the verb and contains no waste. However, given the complexity (5 parameters, 0% schema coverage, no annotations), it is overly terse rather than appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Inadequate for the complexity. With 0% schema coverage, no annotations, and 5 parameters, the description should explain the optional filter behavior and pagination. The existence of an output schema reduces the burden for return value documentation, but parameter and behavioral gaps remain significant.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage. The description compensates partially by mapping 4 parameters to human-readable terms (guest name, listing, etc.), but completely omits the 'limit' parameter and doesn't clarify that all parameters are optional or explain the ID type flexibility (string/number).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Lookup') and resource ('conversations'), and lists the searchable fields. However, it doesn't explicitly distinguish from sibling 'get_conversation_context' (which likely retrieves a single conversation versus searching multiple).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool versus alternatives like 'get_conversation_context' or 'list_unread_guest_threads'. The description lists search criteria but doesn't explain selection logic or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_reservationsC
Lookup reservations by guest name, date range, listing, or reservation id.
| Name | Required | Description | Default |
|---|---|---|---|
| reservationId | No | ||
| guestName | No | ||
| guestEmail | No | ||
| listingId | No | ||
| arrivalStartDate | No | ||
| arrivalEndDate | No | ||
| departureStartDate | No | ||
| departureEndDate | No | ||
| limit | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| total | Yes | |
| results | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full disclosure burden. It doesn't explain what happens when filters are omitted, how the date range logic works (arrival vs departure windows), pagination behavior, or result ordering. The presence of an output schema reduces some burden, but input behavior remains undocumented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with action verb, no redundant phrases. However, extreme brevity is inappropriate given the tool's complexity (9 parameters with zero schema documentation), making it overly terse rather than efficiently concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Inadequate for a 9-parameter search tool with zero schema descriptions and no annotations. Missing critical semantics for date range parameters (which have start/end variants), unmentioned guestEmail parameter, and no explanation of the limit parameter despite its behavioral impact on results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate but falls short. It implicitly covers 7/9 parameters (grouping 4 date fields as 'date range') but completely omits 'guestEmail' and 'limit'. It also fails to explain date formats, exact vs partial matching rules, or that date ranges require paired start/end parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Lookup') with clear resource ('reservations') and lists searchable dimensions (guest name, date range, listing, reservation id). However, it doesn't explicitly differentiate from sibling 'get_reservation_brief', which also retrieves reservation data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this versus 'get_reservation_brief' or other siblings. Doesn't mention that all 9 parameters are optional (0 required) or how to combine filters effectively.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
6 tool updates
v0.1.0- First observed
get_conversation_context - First observed
get_listing_brief - First observed
get_reservation_brief - First observed
list_unread_guest_threads - First observed
search_conversations - First observed
search_reservations
TDQS
Tools are generally well-differentiated by verb (get/search/list) and resource type. While conversation, listing, and reservation domains overlap in hospitality workflows, the tools specify distinct operations (retrieval by ID vs. filtered lists vs. search) that minimize selection errors.
All tools follow a consistent snake_case verb_noun pattern with appropriate verbs (get, list, search). Minor deviation exists in noun choice: two tools use 'brief' while one uses 'context' for similar summary-retrieval purposes, slightly muddling the semantic pattern.
Six tools represent a focused, appropriate scope for guest communication and reservation lookup functionality. The count sits in the ideal range for a specialized retrieval server, avoiding bloat while covering essential read operations.
The surface provides comprehensive read access to conversations, listings, and reservations but lacks write operations such as sending messages, creating reservations, or updating listing status. This read-only limitation creates notable gaps for agents attempting to actively resolve guest issues or modify bookings.
Maintenance
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