respond_collaboration_invite【需要登录】回应 get_my_work 返回的本人定向合作邀请。接受会加入目标并向合作人公开参与关系；婉拒后邀请不再待处理。结果不明或超时后先查询现值，不要自动重发；服务没有持久请求去重键。 接受后用 get_collaboration_goal 核对，待回应列表用 get_my_work。
| Name | Required | Description | Default |
|---|---|---|---|
| accept | Yes | ||
| inviteId | Yes |
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?
Discloses side effects beyond annotations: acceptance joins the goal and exposes participation to the collaborator; rejection removes the invite from pending. Also warns that there is no persistent dedup key and that the agent should query current state on timeout/unknown results, which is critical for a non-idempotent mutation.
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?
Three dense sentences, each adding operational value: scope/auth, behavior, and failure handling. Information is front-loaded with the most important context first.
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?
Fully covers auth, input source, side effects, non-idempotency, timeout guidance, and post-action verification. Given only two simple parameters and existing annotations, nothing essential is missing.
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 0%, so the description must compensate. It does: inviteId is tied to invites returned by get_my_work, and accept true/false maps to accepting or declining. It stops short of explicitly naming the exact field-to-effect mapping, but enough meaning is conveyed.
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 explicitly states the tool responds to collaboration invites from get_my_work and contrasts accept vs reject behaviors. It clearly differentiates from invite_collaboration_member which sends invites.
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?
Provides explicit context: only for personal targeted invites returned by get_my_work, verification via get_collaboration_goal after acceptance, and pending list via get_my_work. Also warns not to auto-resend after unclear outcomes.
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.