Beeper Texts MCP Server

by tetmin

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Server Quality Checklist

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Latest release: v0.0.2
Disambiguation4/5
Tools are mostly distinct with clear purposes. Some overlap exists between search_message_contents and get_person_messages (both return messages), but their descriptions clarify different use cases (text query vs person name). Similarly, list_chats and search_chat_names have overlapping functionality but are distinguished by filtering vs name search.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., search_message_contents, list_chats, get_messages). The verbs are appropriately varied (search, list, get) and predictably used across the set.
Tool Count5/5
Six tools is well-scoped for a messaging server. Each tool fulfills a clear role: searching messages, listing chats, retrieving messages, searching chats, getting person messages, and fetching media attachments. No tool feels redundant or missing.
Completeness2/5
The tool set is entirely read-only, lacking any write operations like sending messages, creating chats, or muting conversations. This is a significant gap for a messaging server, as agents cannot perform basic actions beyond retrieval.
Average 4.1/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on August 11, 2025
- 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.
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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?
No annotations are provided, so the description bears full responsibility for disclosing behavioral traits. It does not state whether the tool is read-only, if it accesses external APIs, or if there are rate limits or pagination. The description only lists parameters and return type, omitting critical behavioral context.
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 reasonably concise, using a clear docstring format with Args and Returns sections. It does not contain extraneous information, though the parameter explanations could be slightly more terse without losing clarity.
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 tool has 6 parameters and an output schema, the description covers the necessary input semantics and return type. However, it lacks context about expected behavior (e.g., whether results are sorted, if empty results are possible) and does not address edge cases or limitations.
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?
The input schema has 0% description coverage, meaning no parameter descriptions within the JSON schema. However, the description includes a full docstring explaining each parameter's purpose, type, and default values. This fully compensates for the schema's lack of descriptions, adding significant semantic value.
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 retrieves messages sent by a specific person across all chats, using a specific verb and resource. This differentiates it from sibling tools like search_message_contents (which searches message content) and get_messages (which retrieves messages by other criteria).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. It does not mention when not to use it, nor does it reference sibling tools. The agent receives no contextual direction for tool selection.
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 full burden. It explains that the tool returns a list of Chat objects and describes parameters, but lacks details on search behavior (e.g., fuzzy matching, case sensitivity), error handling, or rate limits. Some behavioral information is present but not comprehensive.
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 structured with Args and Returns sections, making it easy to scan. It is concise without extraneous words, but could be slightly more front-loaded with the core action. Overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no annotations, and an output schema exists, the description covers the main purpose and parameters but lacks behavioral details like search semantics, edge cases, or guidance on when to use this versus list_chats or search_message_contents. It is adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the input schema for all three parameters, clarifying that query is a partial name match, label filters by chat type with enumerated options, and limit caps results. Since schema coverage is 0%, this provides essential context.
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 searches for chats by name/title with label filtering, using a specific verb and resource. It distinguishes from sibling tools like search_message_contents (searches messages) and list_chats (lists all chats).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool over alternatives or provide when-not-to-use guidance. The context is implied by the tool name and sibling names, but no explicit exclusions or comparisons are given.
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 discloses that messages are chronologically ordered, include metadata, and support filtering. However, it does not mention authentication requirements, rate limits, or any side effects. The description adds context but lacks depth for a read operation.
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 well-structured with a summary line followed by Args and Returns sections. It is concise but not overly brief; every sentence adds value. A minor improvement could be removing the blank line after the summary, but overall it's effective.
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 presence of an output schema (context signals indicate true), the description need not detail returns, but it still summarizes the return type (list of Message objects with metadata). All parameters are documented. The tool has moderate complexity with 4 params, and the description covers filtering, ordering, and return structure adequately.
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?
Schema description coverage is 0%, meaning the schema defines no descriptions. The description fully compensates by explaining each parameter: chat_id, limit, before, after, including defaults and expected formats (ISO-8601 timestamps). This adds significant meaning beyond the schema's bare types.
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 it retrieves chronologically ordered messages from a specific chat with metadata and filtering. The verb 'get' and resource 'messages from a specific chat' are precise. It distinguishes from siblings like search_message_contents and list_chats by focusing on a specific chat's message history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for fetching messages from a chat with optional filters, but it does not explicitly state when to use this tool versus alternatives like search_message_contents or get_person_messages. No exclusions or when-not scenarios are provided.
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 describes the return structure and the include_context parameter but does not explicitly state that this is a read-only operation or discuss any behavioral traits like rate limits, authentication, or idempotency. The search semantics are implied as safe.
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 concise and well-structured, using a clear docstring format with Args and Returns sections. Every sentence adds value with no redundancy. The key information (verb, resource, parameters, return) is front-loaded.
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 moderate complexity (4 parameters, 1 required, simple types) and the presence of an output schema defining return objects, the description is complete. It explains all parameters, the return value, and the scope of the search. No gaps are apparent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, meaning the parameters lack descriptions in the schema. The description compensates by explaining each parameter (query, chat_id, limit, include_context) with their purpose and default values, adding significant meaning beyond the schema's type and default fields.
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 verb 'Search' and the resource 'message contents across all chats', distinguishing it from siblings like search_chat_names (searches chat names) and get_messages (retrieves messages without search). The scope and filtering are explicitly mentioned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching message content with optional filtering, but does not explicitly state when to use this tool versus alternatives like search_chat_names. No exclusivity or when-not conditions are provided, so guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations; description fully covers behavioral traits: resize behavior for images, return types for different media, and error format. Does not mention auth or permissions, but return type details are thorough.
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?
Well-structured with Args and Returns sections. Slightly lengthy but each sentence provides necessary detail. Could be tightened slightly but remains clear.
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?
No output schema; description provides exact return formats for all media types and handles errors. No annotations; description covers behavioral and parameter details completely for a 2-param tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage; description adds meaning with URI format example and purpose of optimize_for_context. Fully compensates for missing 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 retrieves media attachment content by URI from Message.attachments, with a specific URI format. This differentiates it from sibling tools like search_message_contents or get_messages.
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?
Provides clear context for using attachment_uri from Message.attachments and explains the optimize_for_context parameter. Lacks explicit guidance on when not to use it relative to siblings, but the purpose is distinct enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It explains the return format (Chat objects with metadata, truncated messages, participants) and discloses no destructive actions, which is appropriate for a read/list tool. It could mention rate limits or authentication, but given the tool's simplicity, transparency is good.
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 well-structured with a clear summary followed by parameter details. It is slightly verbose but each sentence adds value. The front-loaded purpose is effective.
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 output schema exists, the description still provides a clear explanation of return values. All 6 parameters are documented, and the tool's behavior is fully described. The description is complete for this tool's complexity.
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?
Schema description coverage is 0%, but the description fully compensates by explaining each parameter's meaning, possible values (including enum options for label), and defaults. This adds significant value beyond the schema.
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 lists group and DM chats with metadata, filtering, and sorting. It distinguishes from siblings like search_message_contents and get_messages by focusing on chat listing rather than message search.
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 lists filtering and sorting options but does not explicitly state when to use this tool versus alternatives. However, the sibling tool names imply different scopes (e.g., search_message_contents), providing implicit 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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