Skip to main content
Glama
ACaiSec
by ACaiSec

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation3/5

    The two tools have overlapping purposes focused on retrieving EVM contract information, which creates some ambiguity. While contract_info provides detailed data including view function results and contract_summary offers a quicker overview, an agent might struggle to choose between them for basic needs. The descriptions help clarify the depth difference, but the core domain overlap remains.

    Naming Consistency5/5

    Tool names follow a perfectly consistent pattern with clear verb_noun structure (contract_info, contract_summary). Both use snake_case and share the same prefix ('contract_'), making them predictable and easy to understand. There are no deviations or mixed conventions in the naming scheme.

    Tool Count2/5

    With only 2 tools, the server feels under-scoped for a 'Contract Inspector' domain. While the tools cover information retrieval, there are obvious gaps in functionality like contract interaction, deployment, or verification. A typical contract inspection toolset would include more operations, making this count insufficient for comprehensive use.

    Completeness2/5

    The tool surface is severely incomplete for contract inspection. It only provides read-only information retrieval with no ability to interact with contracts (e.g., call functions with parameters, send transactions), verify source code, or manage deployments. This will cause significant agent failures when trying to perform common contract-related tasks beyond basic queries.

  • Average 3.4/5 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
  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

    If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.

    MCP servers without a LICENSE cannot be installed.

  • 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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation that doesn't call contract functions, which is helpful. However, it doesn't disclose important behavioral traits like whether this requires specific permissions, rate limits, error conditions, or what format the summary information will be returned in. For a tool with zero annotation coverage, this leaves significant gaps.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is appropriately concise with clear sections (purpose, Args, Returns). The first sentence states the core purpose, and subsequent sections efficiently document parameters and returns. There's minimal wasted text, though the structure could be slightly more polished.

    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 has no annotations, no output schema, and only one parameter, the description provides adequate basic information but has clear gaps. It explains the purpose and parameter format well, but doesn't describe what '合约的基本摘要信息' (basic contract summary information) actually contains or provide behavioral context about permissions, errors, or limitations. For a read-only tool, this is minimally viable but incomplete.

    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 meaningful semantic context for the single parameter beyond what the schema provides. While the schema only shows 'contract_address' as a string, the description specifies it must be 'EVM 合约地址 (0x开头的42位十六进制字符串)' - an EVM contract address starting with 0x and 42 hexadecimal characters. This provides crucial format requirements not captured in the schema's 0% description 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 what the tool does ('获取合约基本摘要信息' - get basic contract summary information) with a specific verb and resource. It distinguishes from potential sibling operations by stating '不调用合约函数' (does not call contract functions), though it doesn't explicitly differentiate from the sibling 'contract_info' tool. The purpose is clear but lacks explicit sibling differentiation.

    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 provides some usage context by stating this is for '快速获取合约概况' (quickly get contract overview) and that it doesn't call contract functions. However, it doesn't explicitly state when to use this tool versus the sibling 'contract_info' tool or provide clear alternatives. The guidance is implied rather than explicit.

    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 calling '所有无参数的 view 函数' (all parameterless view functions), which implies read-only behavior, but doesn't explicitly state whether this is a read operation, what permissions are needed, potential rate limits, or error conditions. For a tool that interacts with blockchain contracts without annotation coverage, this leaves significant behavioral gaps.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is well-structured and appropriately sized. It starts with the core purpose, then has clear 'Args' and 'Returns' sections. Every sentence adds value: the purpose statement, parameter explanation, and return description. It could be slightly more concise by combining the purpose and returns, but overall it's efficient.

    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 no annotations, no output schema, and a single parameter with good description coverage, the description is moderately complete. It explains what the tool does and what it returns at a high level ('合约的详细信息,包括基础信息和所有view函数的调用结果' - detailed contract information including basic info and all view function call results). However, for a tool that presumably makes blockchain calls, it lacks details about network behavior, error handling, or response format specifics.

    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 description provides excellent parameter semantics beyond the schema. The schema only shows 'contract_address' as a string with 0% description coverage. The description adds: 'EVM 合约地址 (0x开头的42位十六进制字符串)' (EVM contract address - 42-character hexadecimal string starting with 0x), which gives crucial format and validation details. This fully compensates for the schema's lack of description.

    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: '获取 EVM 合约的完整链上信息,包括调用所有无参数的 view 函数' (Get complete on-chain information for EVM contracts, including calling all parameterless view functions). It specifies the verb ('获取' - get), resource ('EVM 合约' - EVM contract), and scope ('完整链上信息' - complete on-chain information). However, it doesn't explicitly distinguish from its sibling 'contract_summary', which likely provides less detailed information.

    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 through '完整链上信息' (complete on-chain information) and '所有无参数的 view 函数' (all parameterless view functions), suggesting this is for comprehensive analysis rather than a summary. However, it doesn't explicitly state when to use this tool versus 'contract_summary' or provide any exclusion criteria. The guidance is implied rather than explicit.

    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

ContractInfoMCP MCP server

Copy to your README.md:

Score Badge

ContractInfoMCP 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/ACaiSec/ContractInfoMCP'

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