Etherscan MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting different token-related queries, but get_token_holders and get_token_holders_count could be confused as they both retrieve holder information. The descriptions clarify the difference (list vs count), but the overlap in naming might cause misselection.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case (e.g., get_chain_id, get_token_balance). The naming is highly predictable and readable throughout the set, with no deviations in style or convention.
Tool Count4/5
With 6 tools, the count is reasonable for an Etherscan-focused server, covering chain info, RPC endpoints, and token data. It feels slightly thin for a full blockchain explorer, but it's well-scoped for the provided token and chain utilities.
Completeness3/5
The tools cover token balances, holders, and supply, plus chain and RPC info, but there are notable gaps for a broader Etherscan domain. Missing operations include transaction lookups, contract interactions, and gas/price queries, which are common in blockchain tools, limiting coverage to a narrow subset.
Average 3/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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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 states the action ('Get a filtered list') but does not describe key traits like whether it's read-only, if it requires authentication, rate limits, error handling, or the format of the returned list. 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 directly states the tool's function without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse 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 the lack of annotations and output schema, the description is incomplete. It does not explain what the filtered list returns (e.g., format, structure, or example outputs), nor does it cover behavioral aspects like safety or performance. For a tool with no structured support, more contextual detail is needed.
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, clearly documenting all three parameters (chain_id, isOpenSource, tracking) with their types and purposes. The description adds no additional semantic details beyond what the schema provides, such as examples or usage context, 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.
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 ('filtered list of RPC endpoints') with the scope ('for a given chain ID'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'get_chain_id' or 'get_token_balance', which serve different purposes, so it lacks sibling distinction for a perfect score.
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, such as whether it's for querying RPC endpoints specifically or how it relates to other tools like 'get_chain_id'. There is no mention of prerequisites, exclusions, or contextual usage, 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.
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 states the tool's function but lacks critical details: it doesn't specify if this is a read-only operation, what permissions or authentication might be required, potential rate limits, error conditions, or the format of the returned balance. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
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 front-loaded with the core action and resource, making it easy to parse quickly. Every part of the sentence contributes to understanding the tool's function, achieving optimal conciseness.
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 blockchain tool with three parameters and no annotations or output schema, the description is incomplete. It doesn't address behavioral aspects like safety, performance, or error handling, nor does it explain what the output will look like (e.g., numeric balance, units). For a tool in this context, more detail is needed to fully guide 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 input schema has 100% description coverage, with clear documentation for all three parameters (chain_id, token_address, address). The description adds no additional semantic context beyond what the schema provides, such as examples or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but the description doesn't enhance parameter understanding.
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 the balance') and the target resource ('a specific token for a specific address'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'get_token_holders' or 'get_total_supply' by focusing on balance retrieval rather than holder lists or supply metrics. However, it doesn't explicitly mention the blockchain context, which is implied but could be more specific.
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 prerequisites, such as needing valid addresses or chain IDs, or compare it to sibling tools like 'get_token_holders' for different use cases. Without any context on when or why to choose this tool, users must infer usage from the purpose 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 the full burden of behavioral disclosure. It states what the tool does but fails to describe traits like rate limits, error handling, authentication needs, or response format. This leaves significant gaps in understanding how the tool behaves beyond its basic function.
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 unnecessary words. It is front-loaded and wastes no space, making 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 and no output schema, the description is incomplete for a tool with 2 parameters. It lacks details on behavioral traits, response format, and usage context, making it inadequate for full agent understanding despite the concise purpose statement.
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, clearly documenting both parameters. The description adds no additional meaning beyond what the schema provides, such as explaining token address formats or chain ID specifics. Baseline 3 is appropriate as the schema handles parameter documentation adequately.
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 the resource 'number of token holders for a given token address', making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'get_token_holders', which might return detailed holder data rather than just a count, leaving room for ambiguity.
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, such as 'get_token_holders' or 'get_total_supply'. It lacks context on prerequisites, exclusions, or specific scenarios, offering only a basic functional statement without 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 of behavioral disclosure. It states the action ('Get') but doesn't describe traits like whether this is a read-only operation, potential rate limits, error conditions, or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior beyond the basic function.
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 waste. It's appropriately sized and front-loaded, making it easy to understand at a glance. Every word earns its place, contributing to clarity without redundancy.
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 token supply query with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like safety, performance, or return values, which are crucial for an AI agent to use the tool effectively. The description alone is insufficient for full contextual understanding, especially without structured support.
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 adds minimal meaning beyond the input schema, which has 100% coverage with clear descriptions for both parameters ('chain_id' and 'token_address'). It mentions 'token address' aligning with one parameter but doesn't explain 'chain_id' or provide additional context like format examples or constraints. With high schema coverage, the baseline is 3, as the schema does the heavy lifting.
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: 'Get the total supply of a token given its address.' It specifies the verb ('Get'), resource ('total supply of a token'), and key input ('its address'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_token_balance' or 'get_token_holders_count,' which also retrieve token-related data, so it falls short of a perfect score.
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_token_holders_count' or 'get_token_balance,' which might be relevant for related queries, nor does it specify prerequisites or exclusions. Usage is implied by the purpose but lacks explicit context for selection.
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 what the tool does but doesn't describe how it behaves: no information on error handling (e.g., invalid chain names), performance characteristics, authentication needs, rate limits, or what the output looks like. The description is purely functional without behavioral context.
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 lookup tool and front-loads the core purpose immediately. Every word earns its place in communicating the essential function.
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?
For a simple single-parameter lookup tool with no output schema, the description is minimally adequate. It states what the tool does but lacks important context about return format, error conditions, and behavioral characteristics. Given the simplicity of the tool, it's passable but leaves gaps that could affect agent 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?
Schema description coverage is 100%, so the schema already fully documents the single parameter. The description adds no additional meaning beyond what's in the schema (both state it's for getting chain ID for a chain name). Baseline 3 is appropriate when schema does all the parameter documentation work.
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 with a specific verb ('Get') and resource ('chain ID'), and specifies the input parameter ('for a given chain name'). It distinguishes from siblings by focusing on chain ID retrieval rather than token data or RPC lists. However, it doesn't explicitly differentiate from potential similar tools not present in the sibling list.
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 prerequisites, limitations, or comparison with sibling tools like get_filtered_rpc_list (which might provide related network information). Usage is implied by the name and purpose but not explicitly stated.
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 states the tool retrieves token holders but doesn't describe what 'holders' entails (e.g., addresses with balances, excluding zero balances), how data is returned (e.g., list format, pagination), or any limitations (e.g., rate limits, large datasets). For a read operation with no annotation coverage, 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: 'Get the token holders for a given token address'. It is front-loaded with the core action and resource, with zero wasted words. Every part of the sentence earns its place by directly conveying the tool's purpose without redundancy or fluff.
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 (fetching token holders) and the absence of annotations and output schema, the description is minimally complete. It states what the tool does but lacks details on behavior, return values, or usage context. While it covers the basic purpose, it doesn't fully address the gaps left by missing structured data, making it adequate but with clear room for improvement.
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 both parameters ('chain_id' and 'token_address') documented in the schema. The description adds no additional meaning beyond implying the token address is used to fetch holders, which is already clear from the schema. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't detract either.
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: 'Get the token holders for a given token address'. It specifies the verb ('Get') and resource ('token holders'), and distinguishes it from siblings like 'get_token_holders_count' (which counts holders) and 'get_token_balance' (which checks individual balances). However, it doesn't explicitly differentiate from all siblings, such as 'get_total_supply', which might involve similar token data.
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 when to choose this over 'get_token_holders_count' for counting holders or 'get_token_balance' for checking specific balances, nor does it specify prerequisites like needing a valid token address. This lack of context leaves the agent to infer usage from tool names alone.
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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