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local-mcp

by com.local-mcp

Report Problem

report_problem

Sends a problem report, feature request, or integration request to the LMCP team — for when a user wants to report a bug, ask for a new capability, or request support for an app LMCP doesn't cover yet. Without confirm=true it returns a preview of the anonymous payload that would be sent (version, OS, permission status, and recent tool names / error-type codes — never arguments, messages or personal data); with confirm=true it submits and returns a case_id. type='problem' (default) reports a bug, type='feature' requests a new capability, type='integration' requests an unsupported app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confirmNoMust be true to submit the report. Without it, shows a preview.
symptomNoRequired for type=problem: what is broken, in your own words.
expectedNoWhat you or the user expected to happen.
descriptionNoRequired for type=feature or integration: what the user wants.
report_typeNo'problem' (default) | 'feature' | 'integration'
user_requestNoWhat the user originally asked the AI to do.
error_messageNoFor type=problem: verbatim error string from the failed tool.
tool_attemptedNoFor type=problem: name of the LMCP tool that failed.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.1/5.0
Behavior5/5

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

It discloses the key behavioral difference between confirm=true (submits and returns case_id) and without it (preview of anonymous payload). It even describes what the payload contains and excludes. This goes beyond annotations which only say readOnlyHint=false, destructiveHint=false. No contradictions.

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

Conciseness4/5

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

The description is multi-sentence but well-organized, with no filler. Each sentence contributes: purpose, preview/submit behavior, and type semantics.

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

Completeness4/5

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

Given the 8-parameter conditional schema and output schema, the description covers the core behavior and privacy implications. It's enough for an agent to understand the tool's function, though it lacks details on error handling or prerequisites.

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

Parameters3/5

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

All 8 parameters have schema descriptions (100% coverage), so description adds limited extra meaning. It does clarify confirm's role in preview vs submit and explains the three report_type values, but these are also in the schema descriptions. Baseline 3 applies.

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

Purpose4/5

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

The description clearly states it sends problem reports, feature requests, or integration requests to the LMCP team, with specific triggers for each. It does not explicitly distinguish from sibling tools like request_feature or report_friction, but the scope is well-defined.

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

Usage Guidelines4/5

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

The description gives clear contexts: reporting a bug, asking for a new capability, or requesting unsupported app support. It does not mention alternatives or exclusions, so it's missing explicit when-not-to-use guidance.

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