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jun85664396

Pump Fun Data MCP Server

by jun85664396
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation3/5

    The tools have some overlap in purpose, as both get_coins and get_featured_coins retrieve lists of coins, which could cause confusion about when to use each. However, get_coin_info is clearly distinct for retrieving detailed information about a specific coin, and the descriptions help differentiate the list tools by indicating one is for general coins and the other for featured ones.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with 'get_' as the prefix and snake_case throughout (e.g., get_coin_info, get_coins, get_featured_coins). There are no deviations or mixed conventions, making the naming predictable and readable.

    Tool Count2/5

    With only 3 tools, the server feels under-scoped for a data server, as it lacks essential operations like creating, updating, or deleting coins, which are typical for managing data. This minimal set may limit agent functionality and suggests an incomplete surface for the domain.

    Completeness2/5

    The tool surface is severely incomplete for a data server, covering only read operations (get) with no ability to create, update, or delete coins. This creates significant gaps that will likely cause agent failures when trying to perform full data management workflows, such as adding new coins or modifying existing ones.

  • Average 2.7/5 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 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.

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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 only states the action ('Get information') without detailing traits like whether it's read-only, requires authentication, has rate limits, or what happens on errors. This is inadequate 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.

    Conciseness4/5

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

    The description is a single, efficient sentence ('Get information about a coin') that is front-loaded and wastes no words. However, it's overly concise to the point of under-specification, lacking necessary details for full clarity.

    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 simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It doesn't explain what 'information' is returned (e.g., price, metadata), potential errors, or how it differs from siblings, leaving gaps for the agent to navigate.

    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 input schema has 100% description coverage, with the parameter 'mintId' documented as 'The mint id of the coin (coin address)'. The description adds no additional meaning beyond this, such as format examples or constraints, so it meets the baseline for high schema coverage.

    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 ('Get information about a coin') with a clear verb ('Get') and resource ('coin'), but it's vague about what specific information is retrieved. It doesn't distinguish from sibling tools like 'get_coins' (likely lists multiple coins) or 'get_featured_coins' (likely highlights specific coins), missing 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 doesn't mention sibling tools like 'get_coins' or 'get_featured_coins', nor does it specify prerequisites or exclusions, leaving the agent to infer usage from context 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 provided, the description carries full burden but only states basic functionality. It doesn't disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, pagination behavior, or what happens with invalid parameters. For a list tool with 5 parameters, 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.

    Conciseness5/5

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

    The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple list tool and front-loads the core purpose immediately.

    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 5 parameters, the description is incomplete. It doesn't explain return values, error conditions, or behavioral context needed for proper tool invocation. For a tool with this complexity, the description should do more to guide the agent.

    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 all parameters are documented in the schema. The description adds no additional meaning about parameters beyond implying a list operation. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't compensate or enhance understanding.

    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 'Get a list of coins' clearly states the action (get) and resource (coins), but it's vague about scope and doesn't distinguish from siblings like get_coin_info (single coin) or get_featured_coins (filtered subset). It lacks specificity about what kind of list this returns.

    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_coin_info or get_featured_coins. The description doesn't mention any context, prerequisites, or exclusions, leaving the agent to infer usage from parameter names 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?

    No annotations are provided, so the description carries the full burden. It states the action but doesn't disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the return format looks like. This is a significant gap 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 with zero waste. It's front-loaded and appropriately sized for its purpose, 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 complexity of a list-fetching tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'featured' entails, the response structure, or any behavioral context, leaving the agent with insufficient information to use the tool effectively beyond basic parameters.

    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 the parameters (offset, limit, includeNsfw). The description adds no additional meaning beyond what the schema provides, such as explaining why 'featured' coins might be filtered or how parameters interact. Baseline 3 is appropriate when the schema does the heavy lifting.

    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 'Get a list of featured coins' clearly states the verb ('Get') and resource ('featured coins'), but it's vague about what 'featured' means and doesn't distinguish from sibling tools like 'get_coins' or 'get_coin_info'. 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 like 'get_coins' or 'get_coin_info'. The description implies usage for featured coins but doesn't specify context, exclusions, or prerequisites, leaving the agent without clear direction.

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

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