base-security-scanner-mcp

Server Quality Checklist

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Latest release: v1.0.2
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: analyze_bytecode identifies patterns, audit_report generates comprehensive reports, check_honeypot simulates trading, check_token_permissions examines ownership controls, compare_bytecode detects clones, detect_rug_risk scores risk, get_contract_info retrieves metadata, and scan_contract analyzes security issues. The descriptions precisely differentiate their functions, eliminating any ambiguity.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, such as analyze_bytecode, check_honeypot, and detect_rug_risk. This uniformity makes the set predictable and easy to navigate, with no deviations in style or structure across the eight tools.
Tool Count5/5
With 8 tools, the count is well-scoped for a security scanner focused on Base mainnet smart contracts. Each tool serves a specific, necessary function in the domain, from basic metadata retrieval to advanced risk analysis, without being excessive or insufficient for the server's purpose.
Completeness5/5
The tool set provides complete coverage for smart contract security analysis on Base mainnet, including bytecode analysis, honeypot detection, permission checks, risk scoring, contract comparison, metadata retrieval, and comprehensive scanning. There are no obvious gaps; agents can perform end-to-end security assessments without dead ends.
Average 3.6/5 across 8 of 8 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns a similarity score and a boolean for shared code, but does not explain how the comparison works, what the score range means, whether it requires authentication, rate limits, or any side effects. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose and return value with zero wasted words. It is appropriately sized for a tool with two parameters and clear functionality.
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's moderate complexity (comparing bytecode for clone detection), no annotations, and no output schema, the description is minimally complete. It states what the tool does and returns, but lacks details on behavior, usage context, or output interpretation, which are needed for full understanding.
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 already documents both parameters ('address1' and 'address2') as contract addresses. The description adds no additional meaning beyond what the schema provides, such as format requirements or examples, meeting the baseline for high schema coverage.
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's purpose with specific verbs ('compare bytecode') and resources ('two contracts on Base mainnet'), and distinguishes its function from siblings by specifying 'for clone detection' and the return type ('similarity score and whether they share the same code'). This is more specific than generic siblings like 'analyze_bytecode' or 'get_contract_info'.
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 prerequisites, exclusions, or compare it to sibling tools like 'analyze_bytecode' or 'scan_contract', leaving the agent to infer usage context solely from the purpose statement.
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 of behavioral disclosure. While it mentions what the tool analyzes, it does not describe how it behaves—such as whether it requires authentication, has rate limits, returns structured results, or handles errors. For a security analysis tool with zero annotation coverage, this is a significant gap.
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 front-loads the purpose and lists specific security issues without unnecessary words. Every part of the sentence contributes to understanding the tool's function, making it appropriately sized 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 complexity of smart contract security analysis and the lack of annotations and output schema, the description is incomplete. It does not explain what the analysis returns (e.g., report format, severity levels), potential limitations, or prerequisites. For a tool with no structured output and zero annotation coverage, more detail is needed to guide effective 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?
Schema description coverage is 100%, so the schema already documents the single parameter ('address') with its type and description. The description adds no additional parameter semantics beyond what the schema provides, such as format details or validation rules. 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Analyze a smart contract on Base mainnet') and enumerates the security issues it detects ('reentrancy patterns, access control, hidden mints, proxy patterns, and dangerous opcodes'). It distinguishes from siblings by focusing on comprehensive security scanning rather than specific aspects like bytecode analysis or honeypot detection.
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 security analysis of smart contracts on Base mainnet, but does not explicitly state when to use this tool versus alternatives like 'analyze_bytecode' or 'audit_report'. It provides context (smart contract security) but lacks explicit exclusions or comparisons with sibling tools.
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 of behavioral disclosure. It mentions disassembly and pattern identification but lacks details on permissions needed, rate limits, error handling, or what the output looks like (e.g., format, completeness). For a tool with no annotations, this is a significant gap in 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 a single, efficient sentence that front-loads the core action and scope, with no wasted words. It directly communicates the tool's purpose and capabilities without unnecessary elaboration.
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's complexity (analyzing bytecode for patterns) and lack of annotations and output schema, the description is minimally adequate. It covers what the tool does but omits critical behavioral details like output format, limitations, or error cases. Without an output schema, the description should ideally hint at return values, which it does not.
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 'address' parameter clearly documented. The description adds no additional parameter semantics beyond what the schema provides, such as address format or validation rules. Baseline score of 3 is appropriate since the schema does the heavy lifting.
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 specific action ('Disassemble contract bytecode') and resource ('on Base mainnet'), with explicit enumeration of the patterns it identifies (proxy, diamond, AMM, lending, ERC-20, ERC-721, etc). It distinguishes from siblings like 'compare_bytecode' or 'get_contract_info' by focusing on pattern detection rather than comparison or general info retrieval.
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 when you need to analyze bytecode for known patterns on Base mainnet, but it does not explicitly state when to use this tool versus alternatives like 'scan_contract' or 'audit_report'. No exclusions or prerequisites are mentioned, leaving the context somewhat open-ended.
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 mentions the risk score range (0-100) and the types of checks performed, but it lacks details on execution behavior such as rate limits, authentication needs, error handling, or whether the operation is read-only or has side effects, which are critical for a risk assessment 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 front-loaded with the core purpose and efficiently lists the checks in a single, well-structured sentence without any redundant information, making it highly concise and easy to parse.
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's complexity (risk scoring with multiple checks) and the absence of annotations and output schema, the description is moderately complete. It outlines the scoring range and check types, but it lacks details on output format, error cases, or behavioral constraints, leaving gaps for an AI agent to understand full usage.
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 description coverage is 100%, so the schema already documents the token_address parameter. The description adds marginal value by specifying 'on Base mainnet' to reinforce the network context, but it does not provide additional syntax, format, or usage details beyond what the schema provides, meeting the baseline for high coverage.
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's purpose with specific verbs ('Score rug pull risk') and resources ('for a token on Base mainnet'), and it distinguishes from siblings by specifying the comprehensive risk assessment scope (ownership, liquidity, dangerous functions, etc.) that differs from more focused tools like check_honeypot or check_token_permissions.
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 by specifying 'for a token on Base mainnet' and listing the checks performed, but it does not explicitly state when to use this tool versus alternatives like check_honeypot or audit_report, nor does it provide exclusions or prerequisites for usage.
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. While it mentions the types of checks performed, it lacks critical details such as whether this is a read-only operation, potential rate limits, authentication requirements, execution time, or what the output format looks like. For a tool performing multiple security analyses, this is a significant gap in 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 extremely concise and front-loaded, consisting of just two sentences that efficiently convey the tool's purpose and scope. Every word earns its place, with no redundant or unnecessary information.
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's complexity (performing multiple security analyses) and the absence of both annotations and an output schema, the description is incomplete. It adequately explains what the tool does but fails to address behavioral aspects like safety, performance, or output format, which are crucial for a comprehensive audit tool.
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 description coverage is 100%, with the single parameter 'token_address' well-documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema (e.g., it doesn't clarify address format or validation rules), 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Generate a full security audit report') and resource ('for a token on Base mainnet'), with explicit details on what the report includes ('contract scan, honeypot check, rug risk score, bytecode analysis, and permission checks'). It effectively distinguishes this comprehensive tool from its more specialized siblings like 'analyze_bytecode' or 'check_honeypot'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool ('for a token on Base mainnet') and implies it's for comprehensive security auditing. However, it doesn't explicitly state when not to use it or name alternatives (e.g., using individual sibling tools for specific checks), which prevents a perfect score.
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 carries the full burden. It discloses the network (Base mainnet) and specific data returned (contract status, bytecode size, ETH balance, transaction count, token details). However, it lacks information on rate limits, error conditions, or response format, which are important for a tool with no output schema.
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 two concise sentences with zero waste. The first sentence front-loads the core purpose and key data points, while the second adds token-specific details efficiently.
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 and no output schema, the description is moderately complete for a simple query tool. It covers the network scope and data returned, but lacks details on response structure, error handling, or limitations, which are needed for full contextual understanding.
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 already documents the single parameter. The description adds context by specifying the parameter must be a 'Contract or EOA address on Base mainnet', but this is redundant with the schema's description. No additional syntax or format details are provided 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 specific action ('Get basic contract metadata') and resources involved (contracts on Base mainnet). It distinguishes from siblings by specifying the scope of returned data (metadata vs. analysis/audit tools like analyze_bytecode or audit_report).
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 retrieving basic metadata on Base mainnet, but does not explicitly state when to use this tool versus alternatives like scan_contract or check_token_permissions. No exclusions or prerequisites are mentioned.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the simulation method and return values, but does not cover important aspects like rate limits, authentication requirements, error conditions, or whether the simulation consumes resources (e.g., gas fees). The description adds value by explaining the simulation approach but misses key operational details.
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, well-structured sentence that efficiently conveys purpose, method, and outcome without unnecessary words. It is front-loaded with the core action and avoids redundancy, making every part of the sentence earn its place.
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's complexity (simulating transactions), lack of annotations, and no output schema, the description is moderately complete. It covers the what and how but lacks details on behavioral traits (e.g., side effects, performance), error handling, and exact return structure. For a security analysis tool with simulation, more context would be beneficial to ensure safe and correct usage.
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?
Schema description coverage is 100%, so the schema already documents the single parameter ('token_address'). The description adds context by specifying it's for 'Base mainnet' and implies it's used for honeypot checking, but does not provide additional semantic details beyond what the schema states (e.g., format examples, validation rules). Baseline is 3 with high coverage, but the description slightly enhances understanding, warranting a 4.
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 specific action ('Check if a token... is a honeypot'), method ('by simulating buy and sell via Uniswap V2 router'), and outcome ('Returns buy/sell ability and estimated taxes'). It distinguishes itself from sibling tools like 'detect_rug_risk' or 'check_token_permissions' by focusing on honeypot detection via simulation rather than other security analyses.
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 honeypot detection on Base mainnet tokens, but does not explicitly state when to use this tool versus alternatives like 'detect_rug_risk' or 'audit_report'. It provides some context (e.g., 'on Base mainnet', 'via Uniswap V2 router') but lacks clear exclusions or comparative guidance with sibling tools.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool does (checks specific permissions) and implies it's a read-only operation (no destructive actions mentioned). However, it doesn't specify whether this requires blockchain access, rate limits, authentication needs, or what format the results will be in (since no output schema exists).
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 extremely concise and front-loaded, using a single efficient sentence that lists all relevant permissions without unnecessary words. Every element (the action, target, and specific permission checks) earns its place, making it easy to parse while being information-dense.
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's moderate complexity (checking multiple permissions), no annotations, and no output schema, the description does a good job explaining what's being checked but leaves gaps. It doesn't describe the return format, error conditions, or how results are presented. For a permission-checking tool with no structured output documentation, this creates some ambiguity about what the agent should expect.
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%, with the single parameter 'token_address' well-documented in the schema as 'Token contract address on Base mainnet.' The description doesn't add any additional parameter information beyond what's already in the schema, so it meets the baseline score of 3 for high schema coverage.
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's purpose with specific verbs ('check owner permissions') and enumerates the exact permissions being checked (mint, pause, blacklist, change fees, disable trading, ownership renounced). It distinguishes itself from sibling tools like 'get_contract_info' or 'detect_rug_risk' by focusing specifically on permission verification rather than general analysis or risk detection.
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 by specifying what permissions are checked, suggesting it should be used when evaluating token security or ownership control. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_contract_info' (which might include permission data) or 'detect_rug_risk' (which might assess similar risks). No explicit exclusions or prerequisites are mentioned.
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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