Skip to main content
Glama
Cyreslab-AI

FlightRadar MCP Server

by Cyreslab-AI

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation2/5

    The tools 'get_flight_data' and 'get_flight_status' have significant overlap, as flight data typically includes status information, making them ambiguous and prone to misselection. 'search_flights' is more distinct but the other two tools are not clearly differentiated in purpose.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case (e.g., get_flight_data, get_flight_status, search_flights). The naming is predictable and readable throughout the set.

    Tool Count3/5

    With only 3 tools, the count feels thin for a flight radar domain, as it lacks operations like tracking flights by location, getting airport data, or managing alerts. While the tools cover basic queries, the scope seems limited and could benefit from more comprehensive coverage.

    Completeness2/5

    The tool set is severely incomplete for a flight radar server, missing essential operations such as retrieving airport information, tracking flights by geographic area, or accessing historical data. This creates significant gaps that will likely cause agent failures in real-world scenarios.

  • Average 3/5 across 3 of 3 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 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.

  • This repository includes a glama.json configuration file.

  • 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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('search') without any details about permissions, rate limits, pagination, or what the search returns (e.g., flight details, statuses). For a search tool with no annotations, this is insufficient to inform the agent about operational 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, efficient sentence with no wasted words. It is appropriately sized for a simple search tool and front-loads the core action ('search for flights'), making it easy to parse quickly.

    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 (6 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what the search returns (e.g., flight objects, statuses), how results are ordered, or any limitations (e.g., real-time vs. historical data). Without annotations or output schema, the description should provide more context to compensate, but it fails to do so.

    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 schema description coverage is 100%, meaning all parameters are well-documented in the schema itself (e.g., IATA/ICAO codes, flight status with enum, limit with default and max). The description adds no additional parameter semantics beyond 'by various criteria', which is redundant. Baseline is 3 when schema coverage is high, as the schema does the heavy lifting.

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

    Purpose3/5

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

    The description states the purpose as 'Search for flights by various criteria', which is clear but vague. It specifies the verb 'search' and resource 'flights', but lacks specificity about what kind of search or how it differs from sibling tools like 'get_flight_data' or 'get_flight_status'. It doesn't provide enough detail to distinguish it from alternatives.

    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 the sibling tools 'get_flight_data' or 'get_flight_status'. It mentions 'by various criteria', which implies flexibility, but offers no explicit when-to-use or when-not-to-use instructions, leaving the agent to guess based on tool names alone.

    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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Get[s] real-time data,' implying a read operation, but doesn't specify if it requires authentication, has rate limits, returns structured data, or handles errors. For a tool with no annotation coverage, this leaves significant gaps in understanding its operational 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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse quickly. Every part of the sentence contributes essential information, earning its place.

    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?

    Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose but lacks details on usage guidelines, behavioral traits, and how it fits with siblings. Without an output schema, it doesn't explain return values, which is a gap, but the concise purpose statement provides a minimal viable foundation.

    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 minimal meaning beyond the input schema, which has 100% coverage. It implies the tool uses a flight number parameter, but doesn't clarify the relationship between 'flight_iata' and 'flight_icao' or why both are options. Since the schema already documents these parameters well, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.

    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 real-time data for a specific flight by flight number.' It specifies the verb ('Get'), resource ('real-time data'), and scope ('specific flight by flight number'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_flight_status' or 'search_flights', which might offer overlapping functionality.

    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 retrieving data 'by flight number,' but doesn't clarify if this is for a single flight lookup, how it differs from 'get_flight_status' (which might focus on status updates) or 'search_flights' (which could handle broader queries). No exclusions, prerequisites, or context for tool selection are included.

    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, the description carries full burden but only states the basic action without disclosing behavioral traits like data freshness (e.g., real-time vs. cached), error handling (e.g., invalid flight codes), or rate limits. It's minimal and lacks critical operational context.

    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, efficient sentence with zero waste, clearly front-loading the core purpose. It's appropriately sized for a simple lookup tool.

    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?

    Given the tool's low complexity (simple query with two parameters) and full schema coverage, the description is adequate but incomplete due to missing output details (no output schema) and insufficient behavioral context for a tool with no annotations.

    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 the two parameters (flight_iata, flight_icao) and their oneOf logic. The description adds no additional meaning beyond implying flight number usage, meeting the baseline for high schema coverage.

    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 verb ('Get') and resource ('current status of a flight'), making the purpose specific and actionable. It distinguishes from 'get_flight_data' and 'search_flights' by focusing on status retrieval, though it doesn't explicitly differentiate them in the text.

    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 its siblings ('get_flight_data', 'search_flights'), such as for real-time status vs. historical data or search queries. It also lacks prerequisites like flight number availability.

    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

flightradar-mcp-server MCP server

Copy to your README.md:

Score Badge

flightradar-mcp-server 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/Cyreslab-AI/flightradar-mcp-server'

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