Skip to main content
Glama
joemclo

Property Price Search MCP Server

by joemclo

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one looks up postcode data and finds nearest neighbours, while the other searches property price data. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on the task.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with hyphens: 'lookup-postcodes' and 'search-property-prices'. This naming convention is predictable and readable throughout the set.

    Tool Count2/5

    With only 2 tools, the server feels under-scoped for a property price search domain. While the tools cover postcode lookup and price search, there are likely missing operations such as filtering by property features or retrieving detailed property records, making the surface thin and incomplete.

    Completeness2/5

    The server lacks comprehensive coverage for property price search. It includes basic lookup and search functions but misses essential operations like updating or deleting data, advanced analytics, or integration with other property databases, which could lead to agent failures in complex tasks.

  • Average 4.6/5 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

  • 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 effectively describes key behaviors: the tool returns a structured result with center and postcodes data, requires a local database built from specific CSVs, and has default values for 'limit' and 'includeSelf'. It covers output format, prerequisites, and some defaults, though it lacks details on error handling, rate limits, or performance characteristics.

    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 appropriately sized and front-loaded, starting with the core purpose. Every sentence adds value: the first explains the tool's function, the second details input requirements and optional parameters, the third describes the return structure, and the fourth covers prerequisites. There is no redundant information, and the structure flows logically from purpose to usage to output to setup.

    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 complexity (7 parameters, no annotations, no output schema), the description is mostly complete. It covers purpose, input semantics, output format, and prerequisites. However, it lacks explicit error scenarios (e.g., invalid postcodes or coordinates) and does not mention the sibling tool 'search-property-prices' for contextual differentiation, which could enhance completeness for an AI agent.

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

    Parameters5/5

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

    The schema description coverage is 0%, so the description must compensate. It adds significant meaning beyond the schema: it explains that 'postcode' or both 'easting' and 'northing' are needed as the center, describes 'radiusMeters' as in meters, specifies default values for 'limit' (10) and 'includeSelf' (false), and clarifies 'adminDistrict' as a filter. This covers all 7 parameters with practical usage context, fully compensating for the lack of schema descriptions.

    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: 'Look up UK postcodes (Code-Point Open) and find nearest neighbours using OSGB36 eastings/northings.' It specifies the verb ('look up' and 'find nearest neighbours'), the resource ('UK postcodes'), and the coordinate system ('OSGB36 eastings/northings'), distinguishing it from the sibling tool 'search-property-prices' which deals with property prices rather than postcode geolocation.

    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 this tool: to look up UK postcodes and find nearest neighbours based on coordinates. It specifies input requirements ('Provide either `postcode` or both `easting` and `northing` as the center') and optional parameters for filtering. However, it does not explicitly state when not to use it or compare it to alternatives like the sibling tool, which might be relevant for some use cases.

    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 does an excellent job describing the tool's behavior: case-insensitive input handling, uppercasing for queries, pagination support, sorting options, and detailed return format. The only minor gap is not mentioning rate limits or authentication requirements, but overall it provides substantial behavioral 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 efficiently structured and front-loaded with the core purpose, followed by input requirements, optional filters, and return format. Every sentence adds value with no redundancy. Despite covering extensive parameter details, it remains focused and well-organized.

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

    Completeness5/5

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

    Given the complexity (12 parameters, no annotations, no output schema), the description provides exceptional completeness. It covers the tool's purpose, input requirements, all parameter semantics, behavioral details, and the exact return format. For a search tool with rich filtering options, this description gives the agent everything needed to use it correctly.

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

    Parameters5/5

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

    With 0% schema description coverage for 12 parameters, the description fully compensates by explaining every parameter's purpose, format, and constraints. It clarifies the relationship between postcode vs street/city parameters, explains currency units (GBP), provides enum values for propertyType, date format (YYYY-MM-DD), pagination parameters, and sorting options. This adds significant value beyond the bare schema.

    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 ('Search HM Land Registry price-paid data') and resource ('property prices'), distinguishing it from the sibling 'lookup-postcodes' tool by focusing on price data rather than postcode information. It provides a complete picture of what the tool does.

    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 about when to use this tool (searching property price data) and specifies input requirements ('Provide either `postcode` or both `street` and `city`'), but doesn't explicitly mention when NOT to use it or contrast with the sibling 'lookup-postcodes' tool. The guidance is helpful but could be more comprehensive about alternatives.

    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

property-prices-mcp MCP server

Copy to your README.md:

Score Badge

property-prices-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/joemclo/property-prices-mcp'

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