web3-mcp-server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation3/5
The tools have some overlap that could cause confusion, particularly between fetch_balance and fetch_token_balance, as both involve retrieving balances but target different resources (wallet vs. token). However, the descriptions clarify the distinctions, and the other tools (fetch_quote, read_contract) are clearly distinct in purpose.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern using snake_case (e.g., fetch_balance, fetch_quote, fetch_token_balance, read_contract). This uniformity makes the set predictable and easy to understand, with no deviations in naming conventions.
Tool Count3/5With only 4 tools, the server feels slightly thin for a web3 domain, which typically involves more operations like transactions, token transfers, or contract interactions. While the tools cover basic read-only functions, the count is borderline for comprehensive coverage in this scope.
Completeness2/5The tool set is significantly incomplete for a web3 server, as it lacks essential operations such as sending transactions, interacting with smart contracts beyond reading, or managing tokens. This creates gaps that will likely cause agent failures when trying to perform common blockchain tasks.
Average 2.8/5 across 4 of 4 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 full burden for behavioral disclosure. It states 'Read' implying a read-only operation, but doesn't cover critical aspects like authentication needs, rate limits, error handling, or what the output looks like. This is a significant gap for a tool with 5 parameters and 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized for a simple action, though this conciseness comes at the cost of detail, as noted in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (5 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the tool's behavior, parameters, or expected outputs, making it inadequate for an AI agent to use effectively without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but fails to do so. It doesn't explain any of the 5 parameters (e.g., what 'abi' or 'args' represent, how 'chainId' is used), leaving the agent with no semantic understanding beyond the raw schema types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Read a value from a contract' clearly states the action (read) and resource (contract), but it's vague about what constitutes a 'value' and doesn't distinguish this tool from potential siblings like fetch_balance or fetch_token_balance, which might also read contract data. It's not tautological 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 Guidelines2/5Does 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 fetch_balance or fetch_quote, nor does it specify contexts or exclusions for usage, leaving the agent with no direction on tool 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 the full burden of behavioral disclosure. It states a read operation ('Get'), implying non-destructive behavior, but lacks details on permissions, rate limits, error handling, or return format. 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.
Conciseness5/5Is 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'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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (2 required parameters), no annotations, no output schema, and 0% schema coverage, the description is incomplete. It doesn't address parameter meanings, behavioral traits, or output details, leaving significant gaps for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description mentions 'wallet' but doesn't explain the parameters 'walletAddress' or 'chainId', their formats, or purposes. It adds minimal value beyond the schema, failing to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('balance of a wallet'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'fetch_token_balance' or 'read_contract', which might also retrieve balance-related information, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. There are sibling tools like 'fetch_token_balance' that might handle similar queries, but no explicit comparisons or context for selection are given, leaving usage unclear.
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 'Get the price of a token', implying a read-only operation, but doesn't specify details like data source, rate limits, error handling, or response format. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.
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 a single, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a read operation with 1 parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the parameter, expected output, or behavioral traits, making it inadequate for the agent to fully understand how to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, and the tool description doesn't mention the 'slug' parameter at all. This fails to compensate for the lack of schema documentation, leaving the parameter's meaning and usage completely unexplained to the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get the price of a token' clearly states the action (get) and resource (price of a token), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'fetch_balance' or 'fetch_token_balance' which might also retrieve token-related information, so it doesn't fully distinguish itself from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'fetch_balance' or 'read_contract'. It lacks context about specific use cases, prerequisites, or exclusions, leaving the agent with minimal direction for tool 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. 'Get the balance' implies a read-only operation, but it doesn't specify whether this requires authentication, has rate limits, returns cached vs real-time data, or what format the balance comes in. For a 3-parameter tool with zero annotation coverage, this is insufficient.
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 a single, efficient sentence with zero wasted words. It's appropriately sized for a straightforward 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 undocumented parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., numeric balance, formatted string, error conditions) or provide enough context for reliable agent usage beyond the basic purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 3 parameters are documented in the schema. The description doesn't mention any parameters at all, failing to compensate for this gap. The agent must infer parameter meanings from names like 'tokenAddress' and 'chainId' without any semantic guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does 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 'balance of a token', making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'fetch_balance', which appears to be a similar balance-fetching operation, preventing 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 Guidelines2/5Does 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 'fetch_balance' or 'fetch_quote'. There's no mention of prerequisites, context, or exclusions, leaving the agent to guess based on 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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