Skip to main content
Glama
terradeed

TerraDeed MCP Server

Official
by terradeed
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.4

  • Disambiguation5/5

    Each tool serves a clearly distinct purpose: scraping to markdown, extracting structured JSON, and checking wallet balance. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    All tools follow the consistent 'terradeed_verb_noun' pattern (scrape_url, extract_structured, check_wallet). The naming is uniform and predictable.

    Tool Count5/5

    With 3 tools, the server is tightly scoped to its core functions of scraping and extraction. Each tool earns its place, and the count is neither too thin nor too heavy.

    Completeness4/5

    The core workflow of scraping and structured extraction is well-covered. The only minor gap is the lack of schema management or a listing of predefined schemas, but this is not a critical omission.

  • Average 3.9/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 10 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

  • Behavior3/5

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

    The description discloses the cost of $0.05 per call, which is a behavioral trait beyond the schema. However, it does not mention read-only nature, failure behavior, rate limits, or any side effects. Without annotations, this is only partial transparency.

    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 short sentences, each providing useful information (purpose, cost, schema behavior). No extraneous text.

    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 description is adequate for a simple extraction tool without an output schema, but it omits details like the optional instructions parameter, what happens on failure, and any URL limitations. Given no annotations, more context would improve completeness.

    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 100% for all three parameters, so the baseline is 3. The description adds minimal meaning beyond the schema: it reinforces that the schema defines the output fields, but this is largely redundant with the schema 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?

    The description clearly states the tool extracts structured JSON data from a URL using a provided schema, which is a specific verb+resource. It distinguishes from siblings like terradeed_scrape_url by emphasizing structured extraction with a schema rather than a general scrape.

    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 for structured extraction but does not explicitly compare to alternatives like terradeed_scrape_url or state when to use one over the other. No exclusions or prerequisites are given.

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

  • Behavior3/5

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

    No annotations are provided, so the description must convey behavioral traits. It adds the cost per call ($0.01 USDC) and JS rendering support, which are valuable. However, it omits details like rate limits, error behavior, or authentication requirements, 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?

    The description is three short sentences covering purpose, cost, and capability. It is front-loaded with the primary function and contains no 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?

    For a simple scraping tool with no output schema and no annotations, the description provides enough information to understand the main task and return format. It lacks explicit guidance on alternatives and edge cases, but the core function is well covered.

    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 already describes both parameters with full coverage (100%), so the baseline is 3. The description confirms that URLs must be public and mentions JS rendering, but it does not add significant new meaning beyond the 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 verb 'Scrape' and the resource 'any public URL,' with the output 'clean, LLM-ready markdown.' This distinguishes it from siblings like terradeed_extract_structured (structured extraction) and terradeed_check_wallet (wallet check).

    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 gives context that it scrapes public URLs and supports JS rendering but does not explicitly state when to prefer this tool over siblings or any exclusions. Usage is implied rather than explicit, so it falls short of full guidance.

    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 present, so the description must carry the burden of behavioral disclosure. It adds key context by specifying that the tool is free (no x402 payment required) and operates on Base mainnet. It does not explain error handling or return format, but for a simple read-only balance check, this is acceptable.

    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 sentence that front-loads the core purpose and includes only essential additional context (free, network). Every word contributes to understanding.

    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?

    The tool is simple: one optional parameter, no output schema, no annotations. The description provides sufficient information to know what the tool does, under what conditions (free, Base mainnet), and implies the output is the balance. This is complete for a tool of this complexity.

    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 provides a complete description for the address parameter (including default behavior), achieving 100% coverage. The description adds no additional parameter-level information, so the baseline score of 3 is appropriate.

    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 checks the USDC balance of a wallet on Base mainnet, using a specific verb and resource. It also distinguishes itself from sibling tools by focusing on wallet balance rather than URL scraping or structured extraction.

    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 its usage by explaining it checks wallet balance and is free, but it does not explicitly state when to use it over alternatives. The sibling tools are clearly for different purposes, so the intended use is inferred rather than explicitly stated.

    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

terradeed-mcp-server MCP server

Copy to your README.md:

Score Badge

terradeed-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/terradeed/terradeed-mcp-server'

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