invite_memberInvite someone to this brand workspace by email (role: member = read-only on billing, admin = full). This SENDS a real email invite / share link — an account change. Confirm the exact email + role with the user, then call with confirm:true.
| Name | Required | Description | Default |
|---|---|---|---|
| role | No | default member | |
| Yes | the invitee’s email | ||
| confirm | No | REQUIRED true — this invites a real person |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations by explicitly stating 'This SENDS a real email invite / share link — an account change.' This is critical context that readOnlyHint=false alone does not convey. The requirement to call with confirm:true further clarifies the consequence, making the agent fully aware of the irreversible, real-world impact.
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 two concise sentences. The first states the core action and role semantics; the second immediately front-loads the high-stakes nature and the necessary confirmation. No wasted words, and the most important caveat is placed early.
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 simple three-parameter tool with no output schema, the description covers the main purpose, role semantics, and the confirmation requirement. It does not mention prerequisites (e.g., being an admin) or post-invite behavior, but these are not essential for the agent to call it correctly. The explanation is sufficiently complete.
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?
Schema coverage is 100% with each parameter described, but the tool description adds valuable semantics: it explains the role meaning ('member = read-only on billing, admin = full') and reinforces that confirm must be true to send. This enriches the schema descriptions beyond just field labels.
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 uses a specific verb ('Invite') and resource ('someone to this brand workspace by email'), and distinguishes itself from sibling tools like remove_member and set_role by focusing on adding a new member. It also clarifies the role implications ('member = read-only on billing, admin = full'), leaving no ambiguity 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context on when to use the tool ('Invite someone to this brand workspace') and includes a strong usage guideline: 'Confirm the exact email + role with the user, then call with confirm:true.' It does not explicitly compare against alternatives like set_role or remove_member, but the action is unambiguous and the confirmation requirement is a helpful behavioral guideline.
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.
With 293 tools, the surface is enormous and many tools have overlapping purposes—multiple posting tools (post_to_meta, post_to_linkedin, schedule_post, etc.), multiple analytics tools per channel, and several search tools (search_meta_ads, search_instagram, search_reddit...). While each description is detailed, the volume makes it difficult for an agent to reliably distinguish between similar tools without careful reading, leading to frequent misselection.
The naming is largely consistent with a verb_noun pattern (post_to_*, list_*, create_*, delete_*, update_*, manage_*). There are clear families for major operations. A few outliers like 'google_business_account', 'hermoso_capabilities', and 'store_get' break the pattern, but the overwhelming majority follow a predictable structure, making navigation somewhat easier.
293 tools is far beyond any reasonable scope for a single MCP server, even for a comprehensive marketing platform. The calibration guide flags 50+ as an extreme mismatch, and this is nearly six times that threshold. Such a large surface overwhelms context windows, increases the probability of misselection, and makes it impractical for agents to learn or use effectively.
The tool set covers a vast domain: ad creation and rendering, posting across nine+ social channels, analytics and reporting, file management (Drive/OneDrive), competitor research, brand management, and more. It appears to provide CRUD and lifecycle coverage for most resources. While there may be minor gaps given the immense scope, the overall coverage is impressively comprehensive.