apple-messages-mcp-remote
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation3/5
list_chats includes participant info and last message preview, which overlaps with get_chat_participants. Similarly, get_chat_messages and search_messages both retrieve messages, though one is chat-scoped and the other is global. Descriptions help but boundaries are not fully crisp.
Naming Consistency5/5All tool names follow a consistent verb_noun snake_case pattern: list_chats, get_chat_messages, search_messages, send_message, get_chat_participants. No deviations or mixed conventions.
Tool Count5/5Five tools is well-scoped for an iMessage server, covering the core messaging actions without unnecessary bloat. Each tool has a clear place in the workflow.
Completeness4/5The surface covers listing chats, reading message history, searching, sending, and fetching participants. Minor gaps exist such as deleting messages or retrieving a single chat's full metadata, but the essential workflows are complete.
Average 3.3/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Get' implies a read-only operation, but the description does not mention authentication needs, return format, pagination, or any other behavioral traits beyond the trivial verb.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundant words or filler. It is front-loaded and appropriately sized for a tool with one parameter, though it lacks richer context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description does not explain what the participants data looks like, whether it returns names, IDs, or objects, or any edge cases. The description is enough for a trivial call but leaves important operational details unexplained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the single chat_id parameter is fully documented in the schema, including an example format. The description itself adds no parameter-specific meaning, but the schema already covers what is needed, justifying the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'participants of a chat', making the tool's primary purpose obvious. However, it does not differentiate itself from sibling tools such as list_chats or get_chat_messages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives like list_chats or search_messages. The description gives no context, prerequisites, or exclusions, so the agent must infer usage entirely from the tool name and schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the core function and offers no information about read-only behavior, result ordering, pagination, authentication requirements, or what happens when no matches are found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no filler or redundancy. It front-loads the core action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description should provide more operational context. It does not explain whether chat_id is optional for global search, what the response looks like, or how this differs from get_chat_messages. These gaps make the description only minimally viable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all three parameters: query, limit, and chat_id. The description itself adds no parameter-level meaning beyond what the schema already provides, warranting the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search') and the resource ('messages'), with a specific qualifier ('by text content'). It is unambiguous about what the tool does, but it does not explicitly distinguish itself from the sibling tool get_chat_messages, which also involves retrieving messages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives like get_chat_messages or list_chats. It does not mention search scope, such as whether it searches across all chats or within a single chat, nor does it state any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action and does not mention ordering, pagination, date-filter inclusivity, output format, or any permissions/rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence that front-loads the core action and scope. It is economical, though it sacrifices behavioral and usage detail that other dimensions require.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read operation, the description plus the fully described schema is enough to construct a basic call with chat_id and optional filters. However, with no output schema and no guidance differentiating it from search_messages, the agent still faces moderate uncertainty.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and each parameter already has a meaningful description, including default limit, chat_id format, and from/to date filters. The description adds no parameter-specific meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The verb 'Get' and resource 'message history' precisely define the operation, and 'for a specific chat' constrains scope. This clearly distinguishes it from siblings like list_chats and send_message.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a use case—fetching message history for one chat—but gives no explicit guidance on when to prefer it over search_messages, nor any exclusions or alternative routing. The agent must infer selection from tool names and schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden of behavioral disclosure. It mentions that the tool can send to phone numbers or email addresses, but does not explain delivery behavior, error handling, message limits, or whether iMessage automatically falls back to SMS. This leaves significant behavioral ambiguity for a send operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes to explaining the tool's core function, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 fully documented parameters and no output schema, the description covers the essential function but omits practical details like return behavior, error cases, or whether SMS can truly be sent to an email address. The potential ambiguity about iMessage/SMS delivery to email prevents a higher score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters (to, text, service) clearly. The description adds no new parameter meaning beyond restating that recipients are phone numbers or email addresses, which is already in the schema. Baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'send' and the resource 'iMessage or SMS' with recipient types. It is immediately distinguishable from all sibling tools (list_chats, get_chat_messages, search_messages, get_chat_participants), which are read-oriented.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool's purpose through the verb 'send', so an agent can infer that it is for sending messages rather than listing or searching. However, it does not explicitly state when to use this tool versus alternatives, nor does it offer any exclusions or fallback guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It conveys that the operation is a non-mutating list and describes what is returned, but it does not disclose ordering, pagination, result limits, or whether only the current user's chats are included. It does not contradict any annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no wasted words. It efficiently conveys the action, resource, and key return fields, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with one optional parameter and no output schema, the description is reasonably complete: it names the result categories (recent chats, last message preview, participant info). It could add explicit ordering or pagination notes, but the essential information for invoking the tool and understanding its result is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema documents the only parameter, 'limit', with its default value and purpose, so schema coverage is complete at 100%. The description adds no additional 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action ('List') and the resource ('recent chats'), and specifies the included data: last message preview and participant info. It is distinguishable from message-level siblings like get_chat_messages and search_messages, though it does not explicitly name an alternative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The use case is implied: use this when you need an overview of recent chats with message previews and participant details. However, there is no explicit guidance about when to prefer list_chats over get_chat_messages, search_messages, or get_chat_participants, and no exclusions are stated.
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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