neuron_get_eligible_contactsRetrieve contacts eligible to receive a campaign message. Respects deduplication rules and mutual contact requirements.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Unique identifier (UUID) of the campaign to check eligibility for |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral details beyond the annotations, such as respecting deduplication rules and mutual contact requirements, which are not captured in the readOnlyHint, idempotentHint, or destructiveHint. This helps the agent understand critical processing behavior.
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 extremely concise with two short, front-loaded sentences that cover the core purpose and key behavioral notes without any fluff or redundancy.
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?
While the description covers purpose and some behavioral constraints, it does not describe the return value or structure. Since there is no output schema, the agent is left to assume what the response looks like (likely a list of contacts), which is a gap for completeness.
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% for the single parameter 'id,' and the description does not add any extra meaning or usage detail beyond the schema's description of the UUID. The tool description itself does not mention the parameter, so it does not enhance understanding.
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 verb 'Retrieve' and resource 'contacts eligible to receive a campaign message,' and distinguishes itself from sibling tools like 'neuron_get_contact' or 'neuron_search_contacts' by specifying the campaign eligibility context and the additional constraints of deduplication and mutual contact requirements.
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 implies usage context (for campaign messaging) but does not explicitly state when to use this tool versus alternatives such as 'neuron_get_contact' or 'neuron_search_contacts.' It lacks clear guidance on when not to use or which sibling tools might be appropriate for other scenarios.
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.
Most tools are clearly separated by resource type, but there is meaningful overlap in messaging entry points (send_message, send_whatsapp, compose_message, bot_api_send) and contact ingestion/sync tools (import_contacts, populate_contacts, sync_whatsapp_contacts). The descriptions help disambiguate, but with 309 tools an agent will frequently need to read closely to pick the right one.
The overwhelming majority of tools follow a consistent verb_noun snake_case pattern: create_*, get_*, list_*, update_*, delete_*. Minor deviations like sales_stats, lead_stats, wallet_balance, and whoami break the pattern slightly, but overall naming is highly predictable.
309 tools is an extreme count for any MCP server, even a broad platform. This creates significant cognitive load and navigation overhead for agents, and far exceeds the well-scoped 3-15 tool range where coherence is strongest.
The tool surface is remarkably comprehensive across bots, contacts, campaigns, flows, knowledge bases, personas, marketplace, wallet, and products. Minor gaps exist — lead sources lack update/delete tools, and there is no single get_task or get_webhook alongside their list/update/delete counterparts — but these are workable gaps rather than dead ends.