Walrus MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Every tool has a clearly distinct purpose with no ambiguity: delete_blob removes blobs, get_blob retrieves blob content, get_blob_info provides metadata, list_blobs enumerates available blobs, and store_blob uploads new blobs. The actions (delete, get, get_info, list, store) are mutually exclusive and target the same resource type consistently.
Naming Consistency5/5All tools follow a consistent verb_noun pattern with snake_case naming: delete_blob, get_blob, get_blob_info, list_blobs, and store_blob. The verbs are clear and predictable, and the noun 'blob' (or 'blobs') is used uniformly across all tools.
Tool Count5/5With 5 tools, this server is well-scoped for decentralized blob storage operations. Each tool earns its place by covering essential CRUD-like functions (store, get, delete, list) plus metadata retrieval, without being overly sparse or bloated for the domain.
Completeness5/5The tool set provides complete lifecycle coverage for blob storage: store_blob for creation, get_blob for retrieval, get_blob_info for metadata, list_blobs for enumeration, and delete_blob for removal. There are no obvious gaps, and agents can perform all core operations without dead ends.
Average 3/5 across 5 of 5 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
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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 'List stored blobs' but does not reveal key traits: whether it's read-only (implied but not explicit), how results are ordered or paginated, if authentication is required, or potential rate limits. For a list operation with zero annotation coverage, this leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at three words, with zero wasted text. It is front-loaded and directly states the tool's action without unnecessary elaboration, making it efficient for quick comprehension.
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 lack of annotations and output schema, the description is incomplete for a list tool. It does not explain return values (e.g., blob names, metadata, or pagination tokens), error conditions, or dependencies. While the schema covers the single parameter well, the overall context for effective tool use is insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'limit' parameter fully documented. The description does not add any meaning beyond the schema, as it mentions no parameters. According to the rules, when schema coverage is high (>80%), the baseline score is 3 even without parameter info in the description, which applies here.
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 'List stored blobs' clearly states the verb ('List') and resource ('stored blobs'), making the purpose understandable. However, it lacks specificity about scope (e.g., all blobs vs. filtered) and does not distinguish it from sibling tools like 'get_blob' or 'get_blob_info', which might retrieve individual blobs or metadata. This vagueness prevents a higher 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. It does not mention sibling tools like 'get_blob' (for retrieving a specific blob) or 'get_blob_info' (for metadata), nor does it specify contexts such as browsing vs. targeted access. Without any usage instructions, the agent must infer 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.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't disclose if deletion is permanent, requires specific permissions, has rate limits, or what happens on success/failure, which is inadequate for a destructive 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 a single, direct sentence with zero waste, front-loading the core action. It's appropriately sized for a simple tool, 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?
For a destructive tool with no annotations and no output schema, the description is incomplete. It lacks critical context like irreversible effects, error handling, or return values, leaving significant gaps in understanding the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema fully documents the 'blobId' parameter. The description adds no additional meaning beyond implying the parameter is used for deletion, meeting the baseline for high schema coverage without extra value.
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 ('Delete') and resource ('a blob from Walrus storage'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_blob' or 'store_blob' beyond the obvious action difference, missing explicit comparison.
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?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing the blob ID), exclusions, or comparisons to siblings like 'list_blobs' for finding IDs, leaving usage context vague.
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 this is a retrieval operation but doesn't mention whether it requires authentication, has rate limits, returns binary data, or handles errors. For a storage tool with zero 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.
Conciseness5/5Is 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 for a simple retrieval tool and front-loads the essential information.
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 no annotations and no output schema, the description is incomplete for a storage retrieval tool. It doesn't explain what 'blob' means in this context, what format the retrieved data is in, error handling, or authentication requirements. The agent lacks sufficient context to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 'blobId' adequately. The description doesn't add any additional meaning about parameter usage, format, or constraints beyond what the schema provides, 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve') and resource ('a blob from Walrus storage'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_blob_info' which also retrieves blob 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 like 'get_blob_info' (for metadata) or 'list_blobs' (for listing). There's no mention of prerequisites, error conditions, or typical use cases, leaving the agent with insufficient context for optimal 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?
No annotations are provided, so the description carries the full burden. It states the tool retrieves information, implying a read-only operation, but doesn't disclose behavioral traits such as authentication needs, rate limits, error conditions, or what 'availability' entails. For a tool with zero 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get information about a blob') and adds specific details ('size, availability, etc.') without waste. Every word earns its place, making it appropriately sized and well-structured for quick comprehension.
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 tool's low complexity (single parameter, read-only implied), 100% schema coverage, and no output schema, the description is minimally adequate. It covers the basic purpose but lacks context on behavioral aspects (e.g., permissions, errors) and doesn't explain return values. Without annotations, it should do more to compensate, but the simplicity keeps it from being severely incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'blobId' documented in the schema. The description adds no additional meaning about the parameter beyond what the schema provides (e.g., format examples or constraints). With high schema coverage, the baseline score of 3 is appropriate 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('blob'), specifying the type of information retrieved ('size, availability, etc.'). It distinguishes from siblings like 'get_blob' (likely retrieves content) and 'list_blobs' (lists multiple), but doesn't explicitly contrast them. The purpose is specific but lacks explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'get_blob' or 'list_blobs'. It implies usage for retrieving metadata about a specific blob, but offers no explicit context, exclusions, or prerequisites. This leaves the agent to infer usage from the tool name and description 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 of behavioral disclosure. While 'Store' implies a write operation, it fails to describe critical behaviors like whether storage is permanent or reversible, authentication requirements, rate limits, or error conditions. This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is 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 is 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 tool's complexity (a write operation with no annotations and no output schema), the description is incomplete. It lacks details on behavioral traits, error handling, or return values, which are essential for an agent to use this tool effectively in a decentralized storage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, documenting both parameters (data as base64/file path, epochs with default). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 without compensating for any gaps.
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 ('Store') and resource ('a blob in Walrus decentralized storage'), making the purpose immediately understandable. It distinguishes this tool from its siblings (delete_blob, get_blob, etc.) by specifying it's for storage rather than retrieval or deletion.
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 list_blobs or get_blob. It lacks context about prerequisites, such as whether data must be pre-processed or if there are storage limits, leaving the agent without usage 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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