Skip to main content
Glama

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose targeting specific Trello resources: get_boards (boards), get_lists (lists), get_cards (cards in board/list), get_card_details (specific card details), and update_card (modify card). No ambiguity or overlap exists between these operations.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern with snake_case: get_boards, get_card_details, get_cards, get_lists, update_card. The naming is predictable and readable throughout the set.

    Tool Count4/5

    Five tools is reasonable for a Trello server, covering core read operations and one update. It's slightly under-scoped as it lacks create/delete operations for boards, lists, or cards, but the count itself is appropriate for the provided functionality.

    Completeness3/5

    The toolset covers read operations well (boards, lists, cards, card details) and one update (card), but there are notable gaps: no create or delete tools for any resources (boards, lists, cards), and missing operations like moving cards between lists or managing members. This limits full lifecycle management.

  • Average 2.8/5 across 5 of 5 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

  • Behavior1/5

    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 'Get cards' without any details on permissions, rate limits, pagination, or response format. This is inadequate for a tool with potential complexity, as it fails to describe how the tool behaves beyond the basic operation.

    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: 'Get cards from a board or specific list'. It is front-loaded with the core action and resource, with no unnecessary words. This makes it highly concise and well-structured for quick understanding.

    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 no annotations, no output schema, and low schema coverage, the description is incomplete. It does not address behavioral aspects like safety, response handling, or error conditions, and it lacks differentiation from sibling tools. For a tool that likely returns multiple items, more context on output and usage is needed.

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

    Parameters2/5

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

    The input schema has 1 parameter (a nested object with 'board_id' and optional 'list_id'), but schema description coverage is 0%, meaning parameters are undocumented in the schema. The description mentions 'board or specific list', which hints at the parameters but does not explain their semantics, formats, or constraints. This adds minimal value beyond the schema's structure.

    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 tool's purpose as 'Get cards from a board or specific list', which is clear but vague. It specifies the verb 'Get' and resources 'cards', but lacks specificity about scope (e.g., all cards, filtered cards) and does not distinguish from siblings like 'get_card_details' or 'get_lists'. This makes it minimally adequate but with gaps in differentiation.

    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 does not mention when to prefer 'get_cards' over 'get_card_details' for detailed card info or 'get_lists' for list-level operations, nor does it specify prerequisites or exclusions. This leaves the agent without clear usage context.

    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. 'Update' implies a mutation, but it doesn't disclose behavioral traits like required permissions, whether changes are reversible, error handling, or rate limits. It lacks context beyond the basic action, leaving gaps for a mutation tool.

    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's appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration, earning its place as concise and well-structured.

    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 tool's complexity as a mutation with nested parameters, no annotations, no output schema, and 0% schema coverage, the description is incomplete. It doesn't explain what properties can be updated, the response format, or behavioral aspects, making it inadequate for safe and effective use by an AI agent.

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

    Parameters2/5

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

    Schema description coverage is 0%, so the description must compensate. It mentions 'properties of a specific card,' which hints at parameters but doesn't detail card_id or update_data. With 1 parameter (a nested object) and no schema descriptions, the description adds minimal meaning beyond the schema, failing to address the coverage gap.

    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 'Update properties of a specific card' clearly states the verb ('update') and resource ('specific card'), but it's vague about what properties can be updated and doesn't distinguish from sibling tools like get_card_details or get_cards. It provides a basic purpose but lacks specificity.

    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?

    No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, such as needing a card_id from get_cards or get_card_details, or clarify that this is for modifications while siblings are for retrieval. It offers no explicit when/when-not instructions.

    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 the full burden of behavioral disclosure. It states it 'gets' lists, implying a read operation, but doesn't mention any constraints like permissions needed, rate limits, pagination behavior, or what happens if the board_id is invalid. This leaves significant gaps for a tool with no annotation coverage.

    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 any unnecessary words. It's appropriately sized and front-loaded, 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 tool has no annotations, no output schema, and low schema description coverage, the description is incomplete. It doesn't provide enough context about behavior, parameters, or output to adequately guide an AI agent, especially for a tool that interacts with a board system where details like permissions or data format matter.

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

    Parameters2/5

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

    The schema description coverage is 0%, with only one parameter 'board_id' documented in the schema without any description. The tool description doesn't add any parameter details beyond what's implied by 'in a board', failing to compensate for the low coverage. It doesn't explain what format board_id should be in or where to find it.

    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 'all lists in a board', making the purpose immediately understandable. It doesn't distinguish from siblings like 'get_boards' or 'get_cards', but it's specific enough to understand what resource is being retrieved.

    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?

    No guidance is provided on when to use this tool versus alternatives like 'get_boards' or 'get_cards'. The description only states what it does without context about when it's appropriate or what prerequisites might be needed.

    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. It states this is a read operation ('Get'), implying it's likely non-destructive, but doesn't specify permissions required, rate limits, error handling, or what 'detailed information' entails. This leaves significant gaps for a tool that retrieves data.

    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, clear sentence with no wasted words. It's front-loaded with the core action and resource, 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 no annotations, no output schema, and low schema coverage, the description is inadequate. It doesn't explain what 'detailed information' includes, how errors are handled, or any behavioral traits. For a data retrieval tool, this leaves too much uncertainty for reliable agent use.

    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 implies a 'card_id' is needed ('about a specific card'), which aligns with the single parameter in the schema. However, schema description coverage is 0%, so the description adds minimal value beyond what's inferred from the parameter name. It doesn't explain format, validation, or sourcing of the ID.

    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 ('detailed information about a specific card'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_cards' (which might list multiple cards) or 'get_boards'/'get_lists', leaving some ambiguity about scope.

    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 like 'get_cards' or 'update_card'. It doesn't mention prerequisites (e.g., needing a card ID) or contextual factors, leaving the agent to infer usage from the tool name and parameters 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?

    With no annotations, the description carries full burden but only states it retrieves boards without detailing behavior. It lacks information on rate limits, pagination, error handling, or what 'all boards' entails (e.g., archived ones). This is inadequate for a tool with zero annotation coverage.

    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's front-loaded with the core purpose, making it easy to scan and 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 no annotations, no output schema, and a read operation, the description is incomplete. It doesn't explain return values (e.g., board structure), authentication needs, or potential limitations, leaving gaps for an AI agent to use it effectively.

    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 tool has 0 parameters with 100% schema coverage, so no parameter documentation is needed. The description doesn't add param details, but since there are none, a baseline of 4 is appropriate as it doesn't miss anything required.

    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 action ('Get') and resource ('all boards'), specifying it's for the authenticated user. It distinguishes from siblings like get_card_details and get_cards by focusing on boards rather than cards or lists, though it doesn't explicitly contrast with update_card.

    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?

    No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (like authentication), compare with get_lists for list retrieval, or specify scenarios where boards vs. cards are needed, leaving usage context unclear.

    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

mcp-server-ts-trello MCP server

Copy to your README.md:

Score Badge

mcp-server-ts-trello 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/andypost/mcp-server-ts-trello'

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