设置我的通知偏好
set_notification_prefs【需要登录】更新当前用户的通知开关(只传想改的,其余保持不变)。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| dms | No | 私信推送 | |
| drops | No | 新品播报 | |
| nudge | No | 未读私信的邮件/短信触达提醒 | |
| follows | No | 新增关注通知 | |
| matches | No | 新需求与我价值匹配时的撮合推送 | |
| activities | No | 活动通知 |
set_notification_prefs【需要登录】更新当前用户的通知开关(只传想改的,其余保持不变)。
| Name | Required | Description | Default |
|---|---|---|---|
| dms | No | 私信推送 | |
| drops | No | 新品播报 | |
| nudge | No | 未读私信的邮件/短信触达提醒 | |
| follows | No | 新增关注通知 | |
| matches | No | 新需求与我价值匹配时的撮合推送 | |
| activities | No | 活动通知 |
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?
The description adds '需要登录' (login required) and the partial update semantics ('只传想改的,其余保持不变'), both of which are useful behavioral context not present in annotations. It does not contradict the idempotentHint or readOnlyHint 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?
A single sentence delivers the login requirement, the action, the target resource, and the partial-update behavior with no filler. The most critical information is front-loaded.
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?
The description is sufficient for a simple setter with six optional booleans: it covers the operation, authentication need, and update semantics. No output schema exists, but for an idempotent boolean-toggle update, this is acceptable and leaves little ambiguity for the agent.
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 100%, so the schema already documents each boolean parameter's meaning clearly. The description adds the important partial-update behavior, but it does not further elaborate individual parameter semantics, so the baseline of 3 applies.
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 states a specific verb ('更新') and resource ('当前用户的通知开关'), making it clear this tool updates notification preferences for the current user. This distinguishes it from sibling read tools like get_notification_prefs and broader preference tools like set_my_preferences.
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 clearly implies when to use the tool: when the agent needs to modify the current user's notification switches. It provides context through the '当前用户' scope and partial-update behavior, though it does not explicitly name alternatives or when-not-to-use 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.
Each tool has a clearly documented purpose, often with explicit 'when to use' guidance and cross-references, making the vast majority easy to tell apart. A few clusters (get_my_brief, get_my_positioning, get_my_work, get_my_dispatch) and data-overlapping get_my_card vs get_my_profile require careful reading, but descriptions are detailed enough to prevent serious misselection.
The overwhelming majority follow snake_case verb_noun conventions (create_product, update_need, list_my_signups). Minor deviations include noun-only feed names (personalized_feed, random_feed), inconsistency between 'prefs' and 'preferences' in notification tools, and a mix of update_* and set_* for mutations, but the pattern remains predictable overall.
137 tools is an extreme mismatch for any MCP server, far exceeding the 50+ threshold for a score of 1. Even with a broad multi-domain platform, this volume makes tool selection and navigation impractical and heavily burdens the agent's context window.
The surface covers full lifecycles for needs, products, activities/signups, conversations, collaboration goals/tasks, dispatch, profile/onboarding, and supporting resources like companies, parks, policies, and ratings. Deliberate omissions (no user-post creation, no organizer profile editing via agent) are explicitly documented, so core workflows have no obvious dead ends.