Skip to main content
Glama
AkekaratP

Airbnb MCP Server

by AkekaratP
OverviewSchemaRelated ServersScoreDiscussions
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one retrieves detailed information for a specific listing, while the other searches for listings with filters and pagination. There is no overlap or ambiguity between these functions, making it easy for an agent to choose the right tool based on the task.

    Naming Consistency5/5

    Both tool names follow a consistent pattern: 'airbnb_' prefix followed by a descriptive verb_noun combination (listing_details and search). This uniformity enhances readability and predictability, making the tool set easy to understand and use.

    Tool Count2/5

    With only two tools, the server feels under-scoped for an Airbnb domain, which typically involves more operations like booking, user management, reviews, or listing creation. While the tools cover basic retrieval and search, the count is too low to support comprehensive agent workflows, limiting functionality.

    Completeness2/5

    The tool set is severely incomplete for an Airbnb server, lacking essential operations such as booking a listing, managing user accounts, handling reviews, or creating/updating listings. This creates significant gaps that will likely cause agent failures when attempting full interactions with the platform.

  • Average 2.9/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions returning 'detailed information' and 'direct links', which hints at read-only behavior and output format, but fails to address critical aspects like rate limits, authentication needs, error handling, or data freshness. For a tool with 8 parameters and no annotation coverage, this is insufficient.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is brief and front-loaded, stating the core purpose in the first sentence. The second sentence adds a usage hint without redundancy. However, it could be more structured by explicitly separating purpose from guidelines, and the vague phrase 'Provide direct links to the user' slightly reduces clarity.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's complexity (8 parameters, no output schema, no annotations), the description is incomplete. It lacks details on return values, error conditions, performance expectations, and how parameters like dates affect results. Without annotations or output schema, the description should compensate more to ensure the agent can use the tool effectively.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The description adds no parameter-specific information beyond what's already in the schema, which has 100% coverage with clear descriptions for all 8 parameters. This meets the baseline for high schema coverage, but the description doesn't enhance understanding of parameter interactions or provide examples, limiting its added value.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: 'Get detailed information about a specific Airbnb listing.' It specifies the verb ('Get') and resource ('Airbnb listing'), making the intent unambiguous. However, it doesn't explicitly differentiate from its sibling 'airbnb_search' (which likely searches for listings rather than retrieving details for a specific one), preventing a perfect score.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides minimal guidance: 'Provide direct links to the user' suggests a use case for sharing results, but it offers no explicit advice on when to use this tool versus alternatives like 'airbnb_search'. There's no mention of prerequisites, exclusions, or contextual best practices, leaving significant gaps in usage direction.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'pagination' (via the cursor parameter) and 'Provide direct links to the user,' which adds some context about output behavior. However, it lacks critical details such as rate limits, authentication requirements, error handling, or what the search results include (e.g., format, fields). For a search tool with 12 parameters, this is insufficient.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is concise with two sentences that are front-loaded: the first states the core purpose, and the second adds output context. There's no wasted text, but it could be slightly more structured (e.g., separating purpose from behavioral notes).

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the complexity (12 parameters, no output schema, no annotations), the description is incomplete. It lacks details on output format (beyond 'direct links'), error cases, authentication, or rate limits. For a search tool with many filters and pagination, more context is needed to guide effective use by an AI agent.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 100%, so the schema fully documents all 12 parameters. The description adds minimal value beyond the schema, mentioning 'various filters and pagination' which aligns with parameters like location, dates, prices, and cursor. It doesn't provide additional syntax, format details, or usage examples beyond what's in the schema descriptions.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: 'Search for Airbnb listings with various filters and pagination.' It specifies the verb ('search'), resource ('Airbnb listings'), and scope ('with various filters and pagination'). However, it doesn't explicitly differentiate from its sibling tool 'airbnb_listing_details' beyond the general search vs. details distinction.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    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. It mentions 'Provide direct links to the user,' which hints at output format but doesn't clarify usage context, prerequisites, or exclusions. There's no mention of when to choose this over 'airbnb_listing_details' or other potential tools.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

mcp-server-airbnb MCP server

Copy to your README.md:

Score Badge

mcp-server-airbnb MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AkekaratP/mcp-server-airbnb'

If you have feedback or need assistance with the MCP directory API, please join our Discord server