Moltbook MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose targeting specific resources and actions: feed retrieval, post creation/retrieval, commenting, voting, profile access, search, and community listing. There is no overlap or ambiguity between tools, making it easy for an agent to select the correct one.
Naming Consistency5/5
All tool names follow a consistent 'moltbook_' prefix with a descriptive verb_noun pattern (e.g., moltbook_feed, moltbook_post_create, moltbook_search). This uniformity enhances predictability and readability across the toolset.
Tool Count5/5
With 8 tools, the server is well-scoped for a social media platform, covering core functionalities like posting, commenting, voting, browsing, and searching. Each tool serves a clear purpose without redundancy, making the count appropriate for the domain.
Completeness4/5
The toolset provides comprehensive coverage for basic social media interactions, including CRUD-like operations for posts and comments, voting, feed browsing, and community discovery. A minor gap exists in the lack of tools for editing or deleting posts or comments, but agents can still accomplish core workflows effectively.
Average 3/5 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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  ]
}
```
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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 action ('Upvote or downvote') but doesn't explain what this entails—such as whether it requires authentication, affects post visibility or ranking, is reversible, or has rate limits. For a mutation 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste—it directly states the tool's action and target. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly without unnecessary elaboration.
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 tool's complexity (a mutation with 2 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like authentication needs or effects, and with 0% schema coverage, parameter details are insufficient. This leaves the agent with critical gaps in understanding 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.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'post' and 'direction' implicitly but doesn't clarify what 'post_id' represents (e.g., a unique identifier) or that 'direction' accepts 'up' or 'down' values. The description adds minimal value beyond what the schema's property names suggest.
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 ('Upvote or downvote') and the resource ('a post'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential sibling tools like 'moltbook_comment' or 'moltbook_post', which might also interact with posts in different ways.
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 like 'moltbook_comment' or 'moltbook_post'. It lacks context about prerequisites (e.g., needing an existing post) or exclusions (e.g., not for comments or other content types), leaving the agent to infer usage from the tool name 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. It states the action ('Add a comment') but doesn't cover critical aspects like required permissions, whether comments are editable/deletable, rate limits, or response format. 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.
Conciseness5/5
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's front-loaded and appropriately sized for its simple function.
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?
For a mutation tool with no annotations, low schema coverage (33%), and no output schema, the description is inadequate. It doesn't explain behavioral traits, parameter meanings beyond the schema, or what to expect upon success/failure, leaving the agent with insufficient context for reliable 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 low at 33%, with only 'parent_id' having a description. The tool description doesn't add any parameter details beyond the schema, failing to compensate for the coverage gap. However, the baseline is 3 since the schema documents the parameters, even if minimally.
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 ('Add a comment') and target resource ('to a post'), making the purpose immediately understandable. However, it doesn't differentiate this from potential sibling tools like 'moltbook_post' or 'moltbook_post_create', which might also involve post interactions.
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. With siblings like 'moltbook_post' and 'moltbook_post_create', it's unclear if this is the primary commenting method or if there are specific contexts (e.g., replying vs. top-level comments) that warrant its use over others.
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 sorting options but lacks details on permissions, rate limits, pagination, or what the returned posts include (e.g., metadata, content). This is a significant gap for a tool that likely interacts with a social feed.
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—two short sentences that directly state the tool's function and sorting options without any fluff. Every word earns its place, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a social feed tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like authentication needs, error handling, or return format, which are crucial for an agent to use this tool effectively in context.
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 low at 33%, with only the 'submolt' parameter documented. The description adds value by listing the sort options ('hot/new/top/rising'), which clarifies the 'sort' parameter beyond the enum in the schema. However, it doesn't explain the 'limit' parameter or provide additional context for 'submolt', leaving some parameters under-specified.
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 ('posts from Moltbook feed'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'moltbook_search' or 'moltbook_submolts', which might also retrieve posts in different contexts.
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?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't explain how this differs from 'moltbook_search' for finding posts or 'moltbook_submolts' for browsing specific communities, leaving the agent to infer usage from the name 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. It states the tool retrieves a post and includes comments, but doesn't describe error handling (e.g., for invalid IDs), authentication needs, rate limits, or the return format. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
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. It is front-loaded with the core action and includes a useful detail (comments). There is no wasted language, 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 the lack of annotations and output schema, the description is incomplete. It doesn't explain what the return value includes beyond 'comments', such as post content, metadata, or error responses. For a tool with no structured behavioral or output information, the description should provide more context to be fully helpful.
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 'id' parameter documented as 'Post ID'. The description adds no additional meaning beyond this, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the schema already provides adequate parameter information.
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 ('a single post by ID'), specifying it includes comments. It distinguishes from siblings like moltbook_feed (likely lists posts) and moltbook_post_create (creates posts), but doesn't explicitly contrast them. The purpose is specific and actionable, though not fully differentiated from all siblings.
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 it over moltbook_search (which might find posts) or moltbook_feed (which might list posts), nor does it specify prerequisites like needing a valid post ID. Usage is implied by the description 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Create a new post' which implies a write/mutation operation, but doesn't cover critical aspects like authentication requirements, rate limits, error handling, or what happens on success (e.g., returns a post ID). For a creation 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration, making it easy to parse quickly. It's appropriately sized for a simple creation tool.
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 post-creation tool with no annotations, 4 parameters (only 50% documented in schema), no output schema, and multiple sibling tools, the description is insufficient. It doesn't explain return values, error conditions, or how it fits into the broader Moltbook ecosystem. For a mutation tool, more context is needed 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter information beyond what the schema provides. With 50% schema description coverage (only 'content' and 'url' have descriptions), the description doesn't compensate for undocumented parameters like 'title' or 'submolt'. However, since the schema covers half the parameters and the tool has 4 parameters, the baseline is 3, as the description doesn't degrade but also 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 ('Create') and resource ('new post on Moltbook'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'moltbook_post' (which might be for reading/updating posts) or explain what distinguishes a 'post' from other content types like 'comment' or 'feed' entries.
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?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), when not to use it, or how it relates to sibling tools like 'moltbook_post' (which might handle post retrieval) or 'moltbook_comment' (for adding comments). The description is purely functional without contextual advice.
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 search functionality but doesn't disclose behavioral traits such as rate limits, authentication needs, pagination, or what happens on errors. This leaves significant gaps for a tool with potential complexity in handling queries and limits.
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's front-loaded and appropriately sized for a basic search tool, with no wasted content.
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, no output schema, and incomplete parameter coverage, the description is insufficient. It doesn't explain return values, error handling, or behavioral context, making it inadequate for a search tool that likely returns complex results across multiple resource types.
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 50% (only 'q' has a description), and the description adds no parameter-specific information beyond the schema. It implies searching across resources but doesn't clarify how 'q' interacts with 'posts, moltys, and submolts' or the effect of 'limit'. With moderate schema coverage, the baseline is appropriate, but no extra value is added.
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 ('Search') and the resources ('posts, moltys, and submolts'), making the tool's purpose evident. However, it doesn't differentiate from sibling tools like 'moltbook_feed' or 'moltbook_submolts', which might also involve retrieving content, so it lacks sibling distinction.
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. With siblings like 'moltbook_feed' for feeds or 'moltbook_submolts' for specific content, there's no indication of context, exclusions, or prerequisites for choosing this search tool.
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 it's a list operation, implying it's read-only, but doesn't cover aspects like pagination, rate limits, authentication needs, or what 'submolts' entail. This leaves significant gaps for an agent to understand how to use it effectively.
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 fluff or unnecessary words. It's front-loaded and wastes no space, making it highly concise 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 tool has no annotations, no output schema, and the description is minimal, it lacks completeness. It doesn't explain what 'submolts' are, how results are returned, or any behavioral traits, leaving the agent with insufficient context for a list operation.
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?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here, earning a baseline score of 4 for not introducing confusion or redundancy.
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 ('List') and resource ('all submolts (communities)'), making the tool's purpose evident. However, it doesn't differentiate from sibling tools like 'moltbook_feed' or 'moltbook_search', which might also list content, so it's not a perfect 5.
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 like 'moltbook_feed' or 'moltbook_search', nor does it mention any prerequisites or exclusions. It's a basic statement with no contextual usage information.
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 the optional parameter behavior but lacks details on permissions, rate limits, error handling, or what the profile data includes. 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 extremely concise with two short sentences that are front-loaded and waste no words. Every part of the text contributes directly to understanding the tool's purpose and usage, making it highly efficient.
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 doesn't explain what the profile data includes, how errors are handled, or any behavioral traits beyond the basic parameter guidance. For a tool with no structured support, this leaves critical gaps for an AI agent.
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 parameter 'name' fully documented in the input schema. The description adds marginal value by clarifying the semantics of omitting the parameter ('omit for self'), but it doesn't provide additional details beyond what the schema already covers, aligning with the baseline score.
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 as 'Get agent profile' with a specific verb ('Get') and resource ('agent profile'), making it understandable. However, it doesn't explicitly differentiate this tool from potential sibling tools like 'moltbook_search' or 'moltbook_feed', which might also retrieve profile-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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance by stating 'Omit name for your own profile,' which suggests when to use the optional parameter. However, it doesn't offer explicit alternatives (e.g., when to use 'moltbook_search' instead) or broader context for when this tool is preferred over others, leaving room for ambiguity.
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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