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local-mcp

by com.local-mcp

Survey Respond

survey_respond

Shows or submits the short in-product survey Local MCP assigned to this machine. Called with NO arguments it returns the pending survey and, in clients that support MCP Apps, renders it as an interactive card the user answers directly — prefer this. To submit conversational answers instead, pass answers keyed by each question's id (single/scale = one value, multiple = an array of values): call once to PREVIEW, then again with confirm=true to record. Do NOT invent answers — if no human gave them (you're running autonomously), call survey_skip instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
answersNoAnswers keyed by question id. Single/scale = a value; multiple = an array.
confirmNoSet true to actually record the answers. Omit/false = preview only (nothing is stored).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
surveyNoThe pending survey (no-args call) — rendered by the MCP Apps card.
messageNo
previewNo

TDQS

A5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds rich behavioral context beyond the sparse annotations: the tool can both display and record responses, confirm=true is required for persistence, and inventing answers is prohibited. It also discloses the autonomous-agent fallback behavior, giving a clear safety boundary.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every sentence carries essential information: main behavior, preferred mode, submission flow, and safety instruction. It is well-structured and front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's interactive nature, nested answer objects, and output schema, the description is remarkably complete. It covers all invocation modes, the recording semantics, and the alternative for autonomous contexts, leaving no major gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

While the schema already describes both parameters, the description adds crucial semantics: how question types map to value shapes (single/scale vs. multiple), the preview-then-confirm pattern, and the directive not to invent answers. This goes well beyond the bare schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: showing or submitting the short in-product survey assigned to this machine. It distinguishes itself from the sibling tool survey_skip by explicitly directing autonomous agents to use survey_skip instead.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance on when to call with no arguments (preferred interactive path), when to pass answers, the two-step preview/confirm flow, and when to avoid this tool entirely (if no human gave answers, call survey_skip). This fully clarifies usage relative to alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.5/5.0
Disambiguation3/5

Many tools are clearly distinct per app (e.g., chrome_*, safari_*, m365_*), but there is notable overlap between generic file tools like `file_list` and `finder_list`, both listing files; `search_contacts` and `list_contacts` serve similar purposes; `report_friction` and `report_problem` both send feedback to the team. The large number of tools with similar purposes in different domains creates moderate ambiguity for an agent.

Naming Consistency4/5

The naming convention is very consistent overall: most tools follow a `{app}_action` or `verb_noun` pattern (e.g., `chrome_click`, `create_calendar_event`, `list_reminders`). There are minor deviations like `lmcp_install_upgrade` (two verbs) and `complete_omnifocus_task` vs. `complete_reminder` (inconsistent verb placement). Still, the pattern is predictable and readable across the full set.

Tool Count2/5

With 225 tools, the surface is extremely large and heavy. While it covers many distinct domains (browsers, mail, calendar, files, notes, reminders, video editing, web automation, etc.), the sheer number makes it hard to navigate and likely includes many rarely-used tools. This is far beyond the well-scoped range of 3-15 tools and feels excessive even for a 'local everything' MCP server.

Completeness3/5

For many app integrations, the tool set provides solid CRUD coverage (e.g., Calendar has create, read, update, delete; Apple Notes has create, read, update, list, search; OmniFocus has create, list, search, complete). However, some areas are incomplete: for example, there is no tool to create a new Mail folder or delete notes. The 'web' tools lack a clear update/delete for saved sessions. The suite is broad but has notable gaps within individual domains.

Resources