WhatsApp MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: connect_whatsapp handles authentication, list_chats retrieves chat data, and send_message sends messages. There is no overlap in functionality, making it easy for an agent to select the right tool without confusion.
Naming Consistency5/5All tool names follow a consistent snake_case pattern with a verb_noun structure (connect_whatsapp, list_chats, send_message). This predictability enhances readability and usability for agents.
Tool Count3/5With only 3 tools, the server feels thin for a WhatsApp integration, lacking operations like reading messages, managing contacts, or handling media. While the tools cover basic actions, the scope is limited and may require workarounds for common use cases.
Completeness2/5The toolset is significantly incomplete for a WhatsApp server. It misses essential CRUD operations such as reading messages, updating chats, deleting messages, and handling media files. Agents will likely fail when trying to perform common WhatsApp tasks beyond the basics provided.
Average 3.5/5 across 3 of 3 tools scored. Lowest: 2.9/5.
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
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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 tool lists chats but doesn't explain key behaviors: whether this is a read-only operation, what data is returned (e.g., chat metadata, messages), how 'recent' is defined, or if there are rate limits. 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 states the core purpose without any wasted words. It's appropriately sized for a simple list operation and is front-loaded with 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 the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., chat objects, IDs, timestamps), nor does it cover behavioral aspects like error conditions or dependencies. For a tool with no structured metadata, more descriptive context is needed.
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 clearly documented. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline score of 3 where 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 action ('List') and resource ('recent chats from WhatsApp Web'), making the purpose immediately understandable. However, it doesn't differentiate from potential sibling tools like 'connect_whatsapp' or 'send_message', which serve completely different functions, 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 WhatsApp Web must be connected first), nor does it specify what 'recent' means in terms of timeframe or ordering. This leaves the agent with insufficient context for optimal 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?
No annotations are provided, so the description carries the full burden. It mentions the need for an 'exact name', which adds some behavioral context, but fails to disclose critical traits such as authentication requirements, potential rate limits, error handling, or what happens if the chat doesn't exist. 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 action and key requirement ('exact name'). It is front-loaded with no wasted words, 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a mutation operation with no annotations and no output schema, the description is incomplete. It lacks information on behavioral aspects like permissions, side effects, or response format, which are crucial for effective use by an AI agent.
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 both parameters ('chatName' and 'message') with clear descriptions. The description adds minimal value by reinforcing the 'exact name' requirement, but doesn't provide additional syntax or format details beyond what the schema provides.
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 with a specific verb ('send') and resource ('message'), and identifies the target ('chat by its exact name'). It doesn't explicitly differentiate from siblings like 'connect_whatsapp' or 'list_chats', but the action is distinct enough to imply differentiation.
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 implies usage by specifying 'Select a chat by its exact name', suggesting it's for sending messages to known chats. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'list_chats' for finding chats or 'connect_whatsapp' for setup, leaving some ambiguity.
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?
No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: launching a browser, connecting to WhatsApp Web, and the login/verification functionality. However, it lacks details on error handling, timeouts, authentication persistence, or what 'verify' entails. For a tool with no annotations, this is adequate but leaves gaps in operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core action ('Launch browser and connect to WhatsApp Web'), followed by usage guidance. Every word earns its place, with no redundancy or fluff. It efficiently communicates essential information without unnecessary elaboration.
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 complexity (browser automation with login/verification), no annotations, and no output schema, the description is minimally complete. It covers the purpose and usage but lacks details on behavioral outcomes, error conditions, or what success/failure looks like. For a tool with this functionality, more context would be beneficial, but it meets basic requirements.
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 schema description coverage is 100%, so the schema already documents the single parameter 'headless' with its type, default, and description. The description adds no parameter-specific information beyond what's in the schema. With 0 parameters requiring semantic explanation from the description, a baseline of 4 is appropriate as the schema suffices.
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 tool's purpose with specific verbs ('Launch browser', 'connect to WhatsApp Web') and resources ('browser', 'WhatsApp Web'), and distinguishes it from siblings by focusing on connection/login rather than chat listing or messaging. It explicitly mentions the dual use case of 'login or verify if you are already logged in', making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool: 'Use this to login or verify if you are already logged in.' It distinguishes from sibling tools (list_chats, send_message) by implying this is a prerequisite step for accessing WhatsApp functionality, though it doesn't explicitly name alternatives. The guidance is clear and actionable.
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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