xcape

Server Quality Checklist

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

Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: search tools cover different resource types (stays, activities, dining), availability is specific to activities, enrich_place provides details for any place, and the two build tools produce different outputs (a text proposal vs. an interactive HTML page). No two tools overlap in function.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (build_proposal, search_stays, get_activity_availability, enrich_place). The verbs are specific and the nouns clearly indicate the target resource or artifact, making the naming predictable and intuitive.
Tool Count5/5
Seven tools is well-scoped for a travel planning and quoting server. Each tool covers a necessary step in the workflow (searching, availability, enrichment, and output generation) without redundancy or bloat.
Completeness4/5
The surface covers the core trip-planning lifecycle: search stays, activities, dining; check activity availability; enrich places; and generate both a proposal and an options page. Minor gaps exist, such as no dedicated transfer search (transfers are mentioned in build_options_page but not searchable) and no explicit quote generation tool, though these are partially handled within the build tools.
Average 4.2/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses useful behavioral details: party profile mapping to tags, currency-converted prices, and appended affiliate campaign values. However, it does not mention the advisory nature of dates or any rate limits/error behavior, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the action, and every clause adds value. No redundant or promotional language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description adequately summarizes key result fields (rating, price, URL) and behavioral nuances (affiliate tagging). It omits the advisory-date detail, but that is captured in the input schema. Overall complete for a search tool.
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 coverage is high (83%), so baseline is 3. The description adds a little context about profile-to-tag mapping but largely restates schema info; it does not clarify maxResults or other undocumented parameters beyond what schema defaults provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb ('Search') and resource ('tours and activities') with a destination, and it clearly distinguishes from sibling tools like search_stays and search_dining by domain. The Viator API reference adds operational context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies usage for tours/activities searches based on domain, and the sibling tool names (search_stays, search_dining) reinforce differentiation. However, it does not explicitly state when-not-to-use or list alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 reveals that the tool is a scraper, prices are indicative and scraped at quote time, and it can take up to 120s with a specific timeout behavior (returns empty list with a note). These are important behavioral traits beyond what typical search tools might disclose. However, it does not mention potential side effects like external service dependencies or rate limits, so a 4 is warranted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose, followed by two concise caveats (price indicativeness, timeout). Every sentence adds valuable information without excess. It is appropriately sized and structured for quick comprehension by an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 7 parameters, no output schema, and no annotations. The description covers the purpose, data source, and key behavioral traits (timeout, price indicativeness). However, it does not explain the return value structure or what data the agent can expect in a successful response, which is important given the lack of an output schema. The description is adequate for basic usage but leaves gaps for an agent deciding how to use the returned data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 57%, with 4 of 7 parameters having descriptions (checkIn, checkOut, destination, budgetPerNight). The tool description does not add specific meaning for the remaining parameters (adults, children, maxResults), which are self-explanatory by name but lack clarification on limits or behavior. The description only references 'destination and date range' in prose, which is already in the schema. Since the description does not compensate for the low schema coverage, it falls below the baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 vacation stays (hotels/apartments) for a destination and date range via Bright Data's Booking.com listings scraper.' It uses a specific verb (search), identifies the resource (vacation stays), and distinguishes it from siblings like search_activities and search_dining by specifying the domain (stays) and data source (Booking.com scraper).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use the tool: searching accommodation for a destination and date range. It implicitly distinguishes from search_activities and search_dining by focusing on stays. It also notes limitations like price indicativeness and timeout behavior, which help the agent decide if this tool is appropriate. However, it does not explicitly mention alternatives or exclusions, so a 4 is appropriate rather than a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it discloses that the tool writes a file to disk, returns its path, that lodging is 'rate on request', and that priced options come from Viator. It also mentions the interactive 'Generate quote' button and print-to-PDF friendliness. It does not cover edge cases or failure modes, but the core side effects are stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose, and every sentence adds value: first defines the page, second explains the interactive flow and sources, third states the file side effect. No redundant filler or repetition of schema details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 16 parameters and no output schema, the description provides a solid high-level picture: contents, data sources, interactivity, output format, and file writing. It is slightly incomplete regarding whether the tool fetches data itself or expects pre-fetched data from sibling search tools, and it does not detail the structure of the generated HTML page, but it is adequate for most selection decisions.
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 only 38%, so the description must compensate. It adds meaningful context for several parameters (profile-matched experiences, requested day trips, dining, transfers), but leaves many parameters (maxStays, maxActivities, branding, children, etc.) unexplained beyond their schema names. The description gives an overall workflow but not per-parameter semantics, which is a moderate gap given the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Builds') and a clear resource ('self-contained interactive HTML options page for a trip'), listing the major content sections (lodging, transfers, experiences, day trips, dining). It also distinguishes itself from sibling tools by explaining the interactive selection flow and the final quote generation, making its role unique relative to build_proposal.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool by outlining the interactive client selection workflow and mentioning data sources (Google Places, Viator) and output (print-to-PDF quote). It does not explicitly state 'use this when...' or contrast with alternatives like build_proposal, but the context is clear enough for an agent to decide between this and search tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adds crucial context: it is schedule-level (not real-time), prices are converted to agency currency, and booking requires re-confirmation. It implies read-only by saying 'check', but doesn't explicitly state it's non-destructive. The warning about re-confirmation is a valuable behavioral note.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each with a distinct purpose: purpose, conversion detail, and caveat. No redundancy or filler; appropriately sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple, and the description covers purpose, input scope, key behaviors, and a warning. It doesn't specify exact response fields, but 'operating schedule and per-person/total pricing' gives a good indication. Overall, it's sufficient for an agent to use it correctly.
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 covers date and productCodes but not travelers. The description mentions 'per-person/total pricing', which hints at travelers' role, but doesn't explicitly define the parameter or its constraints. Thus it adds some meaning beyond the schema but does not fully compensate for the missing travelers description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Check' with specific resource ('Viator product codes'), scope ('shortlisted'), and time ('specific date'). It also differentiates from sibling tools by referencing the 'search_activities shortlist', making its role obvious.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates this is a follow-up to search_activities, for checking schedule and pricing on shortlisted codes. It also notes the schedule-level nature and advises re-confirmation, which guides the agent on appropriate use. However, it doesn't explicitly mention alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full transparency burden, and it delivers: it discloses parallel execution, ranking criteria, return format (JSON + Markdown), cost breakdown, an indicative-rates disclaimer, and graceful handling of failed provider legs. This goes well beyond a simple 'build a proposal' statement and is genuinely revealing about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence that packs in the composite nature, parallel execution, ranking, output types, cost breakdown, disclaimer, and failure handling. Every clause earns its place with no filler or repetition, making it both concise and information-rich.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity, the absence of annotations, and a missing output schema, the description covers a surprising amount: what the tool does, how it executes, what it returns, and how failures are handled. It falls short only on parameter-level guidance and explicit usage alternatives, which prevents it from being fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 8%, so the description should compensate for the 12 parameters, but it does not. It only loosely references 'profile fit and budget' without explaining the actual parameter names, required fields, formats, or the semantics of options like maxStays or maxDining. This leaves the agent to rely almost entirely on the bare schema, which lacks descriptions for most properties.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific composite action: it runs stays, activities, and dining searches in parallel, ranks results by profile fit and budget, and returns both structured JSON and Markdown. It clearly distinguishes itself from sibling tools like search_stays and search_dining by presenting itself as a one-shot composite rather than a single-domain search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'one-shot composite' clearly indicates this tool is for assembling a full proposal rather than searching a single category, which provides clear context for when to use it. It does not explicitly mention when not to use it or name alternatives, but the parallel-search framing and the sibling list make the intended usage reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 discloses use of pinned, billing-safe field masks (cost control), profile steering behavior, and Google ToS attribution pass-through. This adds meaningful behavioral context beyond the schema, though it does not cover rate limits or return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact (two sentences) and front-loaded with the primary action and resource. Every sentence provides functional value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, the description covers key aspects: purpose, API source, profile steering, billing safety, and attribution requirements. Parameter constraints are handled in the schema (e.g., destination/nearCoordinates orthogonality, maxResults bounds). Minor gaps exist around output shape and edge-case behavior, but overall it supports correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds semantic value to the key required parameter 'profile' by explaining it influences cuisine and price levels. Schema coverage is 60% (destination, priceLevels, nearCoordinates have descriptions), so the description compensates for the otherwise undocumented 'profile' behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Search') and the resource ('restaurants/POIs') and specifies the underlying API ('Google Places API (New)'). It distinguishes itself from sibling tools like 'search_stays' and 'search_activities' by explicitly targeting dining/POI search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this tool is for restaurant/POI search and that the 'profile' parameter steers cuisine type and price levels. It implicitly differentiates from alternatives by content, though it does not explicitly name when not to use it or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It reveals the data returned (website, phone, hours, editorial summary) and the cost implication ('Billed at a higher tier'), adding context beyond the schema. It does not discuss error handling or id validity, but for a simple fetch, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the main action and data fields, followed by a concise cost/usage warning. Every sentence adds value with no repetition or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one param, no output schema), the description covers the key aspects: what is fetched, from where, and when to use it. It does not describe return structure, but that is not expected without an output schema. It is complete enough for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the sole parameter as 'Google place ID from a search_dining shortlist entry' with 100% coverage. The description reinforces this by mentioning 'shortlisted place' and 'shortlist entries', adding clarity to the expected input source without unnecessary detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Fetch Google Place Details' with specific fields (website, phone, hours, editorial summary). It distinguishes itself from sibling search tools by focusing on a single shortlisted place rather than listing options.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'call only for shortlist entries' and warns about the higher billing tier compared to search. This implicitly directs users to use search_dining for initial listing and this tool for enrichment, making the when-to-use context clear.
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

Copy to your README.md:

[![xcape MCP server](https://glama.ai/mcp/servers/ari-systemics/xcape/badges/card.svg)](https://glama.ai/mcp/servers/ari-systemics/xcape)

Score Badge

Copy to your README.md:

[![xcape MCP server](https://glama.ai/mcp/servers/ari-systemics/xcape/badges/score.svg)](https://glama.ai/mcp/servers/ari-systemics/xcape)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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/ari-systemics/xcape'

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