Zappy MCP
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: delete_message removes messages, get_messages retrieves messages, get_status checks connection, list_allowed shows recipients, list_chats enumerates chats, and send_message sends messages. The descriptions reinforce these distinct roles, making misselection unlikely.
Naming Consistency5/5All tools follow a consistent verb_noun naming pattern (e.g., delete_message, get_messages, send_message). There are no deviations in style or convention, making the set predictable and easy to understand at a glance.
Tool Count5/5With 6 tools, the set is well-scoped for managing WhatsApp interactions, covering core operations like messaging, chat/recipient listing, status checks, and deletions. Each tool earns its place without feeling excessive or insufficient for the domain.
Completeness4/5The tool surface covers essential CRUD-like operations for WhatsApp messaging (send, get, delete) and administrative tasks (list chats, list allowed recipients, check status). A minor gap exists in lacking update or permission modification tools, but agents can work around this for basic workflows.
Average 3.5/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 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 is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
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 what the tool does but doesn't describe how it behaves: e.g., whether it's a lightweight check or resource-intensive, if it requires authentication, what happens on failure, or what the return format looks like. This leaves critical operational details unspecified for a tool that likely interacts with an external service.
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 zero waste. It's front-loaded with the core purpose and uses straightforward language. Every word earns its place, 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of checking a client connection status (which may involve network calls, authentication, or error handling), the description is incomplete. With no annotations and no output schema, it doesn't explain what the tool returns (e.g., a status string, boolean, or structured data) or potential side effects. This leaves significant gaps for the agent to understand the tool's full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so there's no parameter documentation needed. The description appropriately doesn't discuss parameters, which is correct for a parameterless tool. A baseline of 4 is applied since the description doesn't need to compensate for any schema gaps.
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 'Check WhatsApp client connection status' clearly states the verb ('Check') and resource ('WhatsApp client connection status'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_chats' or 'get_messages' which might also involve connection status indirectly, 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. It doesn't mention prerequisites (e.g., whether the client must be initialized), when it's appropriate (e.g., before sending messages), or what to do if the status is disconnected. This lack of context leaves the agent guessing about optimal usage scenarios.
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 a permission constraint ('canRead permission'), which is useful, but lacks details on other traits such as rate limits, pagination, error handling, or what 'recent' means in terms of time frame. This leaves significant gaps for a read operation 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 and key constraint without any wasted words. It is appropriately sized and front-loaded, making it easy to understand 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 of a read operation with no annotations and no output schema, the description is incomplete. It lacks information on return values (e.g., message format, ordering), error cases, or behavioral nuances like pagination or rate limits, which are important for effective tool use in this 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 schema description coverage is 100%, so the input schema already documents both parameters ('chatId' and 'limit') adequately. The description doesn't add any additional meaning or context beyond what the schema provides, such as clarifying the format of 'chatId' or usage of 'limit', resulting in a baseline score.
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 ('recent messages from a chat'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_chats' or 'get_status', which prevents 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 Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some context by stating 'Only works for chats with canRead permission', which implies a prerequisite but doesn't offer explicit guidance on when to use this tool versus alternatives like 'list_chats' for broader chat listings or 'send_message' for different actions. The usage is implied rather than clearly defined.
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 but offers minimal behavioral insight. It implies a read-only operation by using 'List,' but doesn't disclose critical details like whether this requires authentication, how data is returned (e.g., pagination), or any rate limits. The description adds some value by specifying the permission fields returned, but lacks depth 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 front-loads the core purpose without any wasted words. It directly states what the tool does and what it returns, 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.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has zero parameters, no output schema, and no annotations, the description is adequate but incomplete. It specifies the resource and returned fields, which helps, but lacks context on system behavior (e.g., authentication needs, data format) that would be crucial for an agent to use it effectively in a real-world scenario.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100%, so the baseline is high. The description adds no parameter information (as there are none), which is appropriate, but it does clarify the output semantics by mentioning the permission fields (canSend, canRead), providing useful context beyond the empty schema.
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 ('List') and the resource ('all allowed recipients with their permissions'), making the tool's purpose immediately understandable. It specifies what information is returned (permissions including canSend, canRead), though it doesn't differentiate from sibling tools like list_chats or get_messages, which prevents 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. It doesn't mention what 'allowed recipients' refers to (e.g., in a messaging system) or how it differs from sibling tools like list_chats or get_messages, leaving the agent to infer 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. While it mentions the tool lists chats with IDs and permissions, it doesn't describe key behavioral traits such as whether this is a read-only operation (implied but not stated), potential rate limits, authentication requirements, or how permissions are formatted. For a 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 extremely concise and well-structured with two sentences. The first sentence states the core purpose, and the second provides usage guidance. Every word earns its place, with no redundancy or unnecessary information, making it easy to parse quickly.
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 moderate complexity (2 parameters, no output schema, no annotations), the description is partially complete. It covers the purpose and a usage scenario but lacks details on behavioral aspects like safety, authentication, or output format. Without annotations or an output schema, more context on what 'permissions' entail or how results are structured would improve completeness, leaving it at an adequate but minimal level.
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%, meaning both parameters ('limit' and 'groupsOnly') are fully documented in the schema. The description doesn't add any parameter-specific information beyond what the schema provides (e.g., it doesn't explain the semantics of 'groupsOnly' or default values). With high schema coverage, the baseline score is 3, as the description doesn't compensate but also doesn't detract.
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 tool's purpose: 'List all WhatsApp chats with their IDs and permissions.' It specifies the verb ('List'), resource ('WhatsApp chats'), and what information is returned ('IDs and permissions'). However, it doesn't explicitly differentiate from sibling tools like 'get_messages' or 'list_allowed', which prevents 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 Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: 'Use this to find chat IDs for config.json setup.' This gives a specific scenario for when to use the tool. However, it doesn't mention when NOT to use it or explicitly compare it to alternatives like 'get_messages' (which might retrieve message content rather than chat metadata), so it falls short of 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?
With no annotations, the description carries full burden. It discloses key behavioral traits: it's a mutation tool (implied by 'send'), has a failure condition ('Will fail if recipient is not in the allowed list'), and hints at auth/access control. However, it lacks details on rate limits, response format, or error handling, leaving gaps for a tool with no annotations.
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?
Two sentences, zero waste. First sentence states purpose and scope, second sentence adds critical behavioral constraint. Every word earns its place, and information is front-loaded appropriately.
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 no annotations and no output schema, the description is moderately complete. It covers the core action and a key constraint, but lacks details on return values, error types, or side effects. For a mutation tool with 2 parameters, this is adequate but has clear gaps, scoring a minimum viable 3.
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%, with both parameters well-documented in the schema. The description adds no additional parameter semantics beyond what's in the schema (e.g., no extra format details or examples). Baseline 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 'send' and resource 'WhatsApp message', specifying the target as 'an ALLOWED phone number or group'. It distinguishes from siblings like 'get_messages' (read) and 'delete_message' (delete), though not explicitly named. However, it doesn't fully differentiate from hypothetical similar send tools, keeping it at 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use: 'to an ALLOWED phone number or group'. It implies an alternative (check allowed list first via 'list_allowed') but doesn't explicitly name it or state when not to use. No misleading guidance is present, making it a solid 4.
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 permission requirements ('Requires canDelete permission') and ownership constraints ('Can only delete messages sent by you'), which are crucial behavioral traits for a destructive operation. However, it doesn't mention potential side effects, error conditions, or what happens when 'forEveryone' is set to false.
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 (two sentences) with zero wasted words. It's front-loaded with the core purpose and efficiently communicates essential constraints. Every sentence earns its place by providing critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given 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 does well by covering permission requirements and ownership constraints. However, it doesn't explain what happens after deletion (e.g., confirmation, error messages) or the implications of the 'forEveryone' parameter, leaving some behavioral gaps.
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%, so all parameters are 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 explain the implications of 'forEveryone' or how to obtain 'chatId' and 'messageId'). The baseline score of 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.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Delete a message') with the resource ('message'), distinguishing it from sibling tools like 'send_message' or 'get_messages'. It's precise and unambiguous about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool ('Can only delete messages sent by you') and mentions a prerequisite ('Requires canDelete permission'), but doesn't explicitly state when NOT to use it or name alternatives among the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/brendandebeasi/zappy-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server