PancakeSwap PoolSpy MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.
Naming Consistency5/5A single tool inherently has perfect naming consistency, as there are no other tools to compare against. The name 'get_new_pools_bsc' follows a clear verb_noun_domain pattern.
Tool Count2/5One tool is too few for a server focused on monitoring PancakeSwap pools, as it lacks essential operations like retrieving pool details, tracking liquidity changes, or analyzing historical data. This severely limits the server's utility for comprehensive agent workflows.
Completeness2/5The tool surface is severely incomplete for the PancakeSwap monitoring domain. While it covers new pool discovery, it lacks tools for querying existing pools, checking pool metrics (e.g., volume, fees), or performing deeper analysis, leaving significant gaps that will hinder agent tasks.
Average 3.7/5 across 1 of 1 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.
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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. It describes the retrieval behavior but lacks details on potential side effects (e.g., rate limits, authentication needs, data freshness, or error handling). While it specifies the scope (new pools in a time range), it does not disclose behavioral traits like pagination, sorting, or what happens if no pools are found, leaving gaps for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by a structured parameter list with clear explanations and defaults. Every sentence adds value without redundancy, making it efficient and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a read operation with two parameters), no annotations, and no output schema, the description is moderately complete. It covers the purpose and parameters well but lacks details on return values (e.g., pool structure, fields) and behavioral aspects like error handling or performance. This leaves some gaps for an agent to use the tool effectively without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 adds meaningful semantics by explaining that 'time_range_seconds' is 'the time range in seconds to look back for new pools' with a default, and 'limit' is 'the maximum number of pools to return' with a default. This clarifies the purpose and usage of both parameters beyond what the schema provides, though it could include more on constraints (e.g., min/max values).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Returns a list'), resource ('trading pools'), and scope ('created in the specified time range on Pancake Swap V3 BNB Smart Chain'). It distinguishes this as a retrieval operation for newly created pools with temporal filtering, making the purpose immediately understandable without redundancy.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by specifying the time range for new pools, but it does not provide explicit guidance on when to use this tool versus alternatives (e.g., for historical vs. real-time data, or other filtering criteria). Since no sibling tools are listed, the lack of comparative guidance is less critical, but it still lacks explicit when/when-not directives.
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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