Generate a personalized LinkedIn connection note (max 300 characters). Fetches lead profile, campaign goal, ICP, and persona data from Convex, then uses AI to craft a short, compelling connection note. Use for connection requests. For first messages after connecting, use campaignstack_craft_message.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 already indicate readOnlyHint=true and destructiveHint=false. The description adds useful behavioral context beyond annotations: it fetches lead profile, campaign goal, ICP, and persona data from Convex, and uses AI to generate the note. It also clarifies the tool only generates text rather than sending the connection request, which is valuable.
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 compact, front-loads the key purpose and character limit, and devotes its second sentence to routing the agent to the correct sibling. Every sentence earns its place without unnecessary detail.
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?
For a zero-parameter generation tool, the description explains what it produces, the data sources it uses, the length limit, and when to use it vs. an alternative. It could be slightly clearer about how the target lead/campaign is selected given no explicit parameters, but overall it is sufficient for correct invocation.
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 tool has zero parameters, so the schema carries no burden. The description adds meaning by explaining that the tool automatically draws on lead profile, campaign goal, ICP, and persona data from Convex, effectively clarifying how input context is resolved despite the empty parameter list.
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?
Description clearly states the specific action ('Generate'), the resource ('personalized LinkedIn connection note'), and the explicit constraint ('max 300 characters'). It also differentiates from nearby siblings by naming the alternative use case for first messages via campaignstack_craft_message.
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?
Explicitly says 'Use for connection requests' and gives the when-not-to-use condition: 'For first messages after connecting, use campaignstack_craft_message.' This provides clear exclusions and routes to the correct sibling, leaving no inference needed.
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.
Many tools share the same verb prefix (create_, list_, update_, get_) across closely related resources, so pairs like add_lead_to_external_list vs add_lead_to_sequence, create_signal_agent vs create_signal_watch, and approve_review vs approve_content_post can be confused. The descriptions are unusually detailed and cross-referenced, which mitigates but does not eliminate the ambiguity inherent in a 282-tool surface.
Virtually every tool follows the campaignstack_verb_noun snake_case pattern, which is highly predictable. Minor deviations exist: destructive operations mix remove_ and delete_ (remove_lead_list vs delete_campaign), AI generation uses both craft_ and generate_, and the seo_/search_console_ subdomains introduce a second prefix convention.
282 tools is an extreme mismatch by any reasonable standard, exceeding the 50+ threshold by more than 5x. Even for a full B2B outreach platform, this surface is far too large and would be better consolidated into higher-level operations or grouped sub-servers.
The tool surface is impressively comprehensive, covering campaigns, workflows, leads, content, ads, SEO, integrations, billing, and more with CRUD-level depth. Minor gaps remain: no single-ICP getter, no direct pause/delete for search watches, and no explicit delete for ad campaigns (only archive via update).
