Skip to main content
Glama
kevinwuhoo

Google Maps Geocoding MCP Server

by kevinwuhoo

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.2

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: geocode_forward handles addresses to coordinates, geocode_place converts Place IDs to addresses, and geocode_reverse does coordinates to addresses. There is no overlap or ambiguity between these three operations.

    Naming Consistency5/5

    All tool names follow a consistent 'geocode_' prefix with descriptive suffixes (forward, place, reverse), using snake_case uniformly. This pattern is predictable and enhances readability.

    Tool Count5/5

    With 3 tools, the server is well-scoped for geocoding operations, covering the essential forward, reverse, and Place ID conversions. Each tool earns its place without being excessive or insufficient for the domain.

    Completeness5/5

    The tool set provides complete coverage for the Google Maps Geocoding domain, including forward geocoding, reverse geocoding, and Place ID resolution. There are no obvious gaps, as these are the core operations offered by the API.

  • Average 3.2/5 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.

  • 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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the API used but does not cover critical traits such as rate limits, authentication requirements, error handling, or response format. For a tool with no annotations, 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 function without unnecessary words. It is front-loaded with the core purpose and uses clear terminology, making it easy to understand 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 of a geocoding tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., API constraints), output format, and differentiation from siblings. While the schema covers parameters well, the overall context for effective tool use is insufficient.

    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%, meaning all parameters are documented in the input schema with descriptions. The description adds no additional semantic details about parameters beyond what the schema provides, such as examples or usage tips. With high schema coverage, the baseline score of 3 is appropriate as the description does not compensate but also does not detract.

    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: converting a Google Place ID to a human-readable address using the Google Maps Geocoding API. It specifies the verb ('Convert'), resource ('Google Place ID'), and target ('human-readable address'), but does not explicitly differentiate from sibling tools like geocode_forward or geocode_reverse, which likely handle different inputs (e.g., addresses or coordinates).

    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 (geocode_forward and geocode_reverse), nor does it mention any prerequisites, exclusions, or alternative scenarios. It only states what the tool does without contextual usage information.

    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 full burden for behavioral disclosure. While it mentions the external API being used, it doesn't disclose important behavioral traits like rate limits, authentication requirements, error handling, cost implications, or what happens with ambiguous addresses. The description is minimal and lacks 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 that communicates the core purpose without any wasted words. It's appropriately sized for a straightforward geocoding operation and is front-loaded with the essential information.

    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?

    For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the return values look like (coordinates format, confidence levels, multiple results handling), doesn't mention error cases or limitations, and provides no context about the external API's constraints or behavior.

    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 already documents all 7 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. The baseline of 3 is appropriate when the schema does all the parameter documentation work.

    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 specific action ('Convert an address to geographic coordinates') and identifies the exact resource ('using Google Maps Geocoding API'). It distinguishes from sibling tools by specifying forward geocoding (address→coordinates) versus reverse geocoding or place-based geocoding.

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

    Usage Guidelines3/5

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

    The description implies usage context (forward geocoding) but doesn't explicitly state when to use this tool versus the sibling tools 'geocode_place' or 'geocode_reverse'. No guidance is provided about alternative approaches or when not to use this tool.

    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 full burden. It mentions the external API but does not disclose behavioral traits such as rate limits, authentication needs, error handling, or response format. This leaves significant gaps for a tool interacting with an external service.

    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. It is front-loaded with the core purpose and uses clear, direct language without redundancy.

    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 of an external API tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., rate limits, errors) and output format, which are critical for proper tool invocation and integration.

    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 5 parameters. The description adds no additional parameter semantics beyond what the schema provides, such as explaining interactions between parameters or usage examples. Baseline 3 is appropriate when schema does the heavy lifting.

    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 specific action ('Convert geographic coordinates to a human-readable address'), identifies the resource ('using Google Maps Geocoding API'), and distinguishes from siblings by specifying reverse geocoding (vs. forward geocoding or place geocoding).

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

    Usage Guidelines3/5

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

    The description implies usage context (when coordinates need conversion to addresses) but does not explicitly state when to use this tool versus alternatives like 'geocode_forward' or 'geocode_place'. It lacks explicit guidance on exclusions or prerequisites.

    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

google-maps-geocoding-mcp MCP server

Copy to your README.md:

Score Badge

google-maps-geocoding-mcp 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/kevinwuhoo/google-maps-geocoding-mcp'

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