neuron_webagent_list_runsList browser-mission runs (live + recent). Stale runs (no heartbeat >2min) show as 'stale'. Note the result nests as data.data[].
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No | ||
| status | No | Filter by status. |
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 establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds non-obvious behavioral details: stale runs are defined by a >2min heartbeat threshold, and the response nests under data.data[]. This goes beyond what the schema or annotations provide.
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 tight and front-loaded: scope comes first, the stale behavior follows, and the response-nesting caveat is last. Every sentence contributes useful information with no filler.
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 read-only list operation with optional pagination and status filters, the description covers the two most important API quirks: stale detection and the data.data[] wrapper. It omits pagination defaults and result ordering, but an agent has enough to select and invoke 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?
Schema description coverage is low at 33%, and the description adds no parameter-level detail. Only 'status' has a schema description; page and limit rely on their type/min/max constraints without semantic explanation. The stale-run text helps clarify the 'stale' enum value but does not compensate for the overall gap.
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 states a specific verb and resource: 'List browser-mission runs', and adds scope with '(live + recent)'. The stale-run heartbeat detail further defines the list's contents and helps distinguish it from singular tools like neuron_webagent_get_run and other run-list tools.
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 intended use is implied by the imperative 'List', but the description gives no explicit guidance on when to choose this over sibling tools such as neuron_webagent_get_run or neuron_webagent_command_history. It provides context about what is included but no exclusions or alternatives.
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.