MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token. Best: add it to this server's config as a header Authorization: Bearer <token> for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "" } after the user pastes, or with no args to get the link.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate idempotentHint=true and destructiveHint=false, which the description aligns with. The description adds behavioral context: it explains that calling with no args returns a link, and that pasting a token provides session-only login. It also clarifies the token is a JWT and how to use it. However, it doesn't explicitly state that the tool is non-destructive or idempotent, but the annotations already cover that, so the description adds value beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the tool's purpose, and every sentence adds value. It covers the two usage modes and the token parameter without unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter, no output schema), the description is complete enough. It explains the authentication flow, the two methods, and the token parameter. It could mention what the response looks like, but since there's no output schema, the description doesn't need to detail return values. The context is sufficient for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one optional parameter 'token' with no description, and schema description coverage is 0%. The description compensates by explaining the token parameter: it should be a JWT pasted by the user, and calling without it returns the login link. This adds meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to authenticate an IDE agent (like Cursor) by logging in via browser and obtaining an access token. It distinguishes itself from siblings like 'connect' and 'marketplace' by focusing specifically on authentication flow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: it explains two methods (permanent config-based token vs session-only token), when to call with no args to get the link, and when to call with the token. It also mentions the alternative of adding the token to the server config for a permanent connection, which helps the agent decide between approaches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
There are many flattened action variants (e.g., whatsapp_chat_archive, whatsapp_chat_unarchive, whatsapp_chat_pin, etc.) that duplicate the same underlying action with similar descriptions, making it easy to select the wrong tool. However, some tools like whatsapp_send_text vs whatsapp_send_media are clearly distinct, and the group management tools share a common action pattern.
Most tools follow a consistent `whatsapp_<resource>_<action>` pattern (e.g., whatsapp_chats, whatsapp_messages, whatsapp_group_members), with flattening creating multiple tools from the same action set. A few exceptions like `authenticate`, `connect`, `marketplace` break the pattern, but the WhatsApp-specific tools are largely consistent.
47 tools is substantial, and many are flattened action variants (e.g., 6 chat state tools for archive/unarchive/pin/unpin/mute/unmute) that could be consolidated. The sheer number makes the tool list difficult to navigate, especially with non-WhatsApp tools like authenticate, marketplace, and report_bug mixed in. This feels over-scoped for a WhatsApp server.
The tool set covers core WhatsApp workflows: reading chats, contacts, groups, messages, sending messages/media, reacting, polls, search, history backfill, webhooks, and config. Minor gaps include lack of explicit voice message sending and perhaps advanced group settings, but most lifecycle operations are present.