Second Brain MCP

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool serves a unique function: remember adds content, recall searches, library lists, transcript retrieves raw text, digest summarizes recent additions, and forget deletes. No two tools overlap in purpose, and their descriptions clarify the distinct use cases.
Naming Consistency4/5
Most tool names are single-word imperative verbs (remember, recall, digest, forget), giving a clear action-oriented pattern. However, 'library' and 'transcript' are nouns, breaking the otherwise consistent verb style, though still predictable in context.
Tool Count5/5
With six tools, the set is well-scoped for a personal knowledge management server. Each tool addresses a core need—adding, searching, listing, reading, summarizing, and deleting—without unnecessary bloat or overlap.
Completeness5/5
The tool surface covers the full lifecycle for stored media: creation (remember), retrieval (recall, library, transcript), summarization (digest), and deletion (forget). There are no obvious gaps or dead ends; the only potential missing operation is update, but it's not essential for this domain.
Average 4/5 across 6 of 6 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
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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?
The description discloses 'newest first' as a sorting behavior but omits the fact that the 'limit' parameter (default 25) constrains the result set. This is a significant behavioral omission that could mislead an agent into thinking all stored items are returned when actually only a limited subset is.
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 one concise sentence that efficiently states the core action and ordering. Every word contributes meaning, and it is appropriately front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even though the tool has only one optional parameter and an output schema exists, the description fails to mention the limiting behavior or provide any usage context. The agent cannot fully anticipate the output scope or how to request larger result sets.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema defines 'limit' with a default but provides no description, and the tool description does not mention or explain this parameter. With 0% schema description coverage, the agent cannot accurately understand what 'limit' does or how it affects results.
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 uses a specific verb 'List' and identifies the resource as 'everything stored in the second brain,' with ordering 'newest first.' It clearly conveys a comprehensive listing action and implicitly distinguishes from more targeted sibling tools like 'recall' or 'remember.'
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 provides no guidance on when to use this tool versus siblings like 'recall' or 'digest.' It lacks explicit alternatives, exclusions, or context for appropriate use, leaving the agent to infer when 'library' is the right choice.
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 must disclose behavioral traits. It states the core action but does not mention whether it is read-only, what the summary contains, how the 'N days' parameter behaves, or any other side effects. It provides minimal additional context beyond what the name and schema suggest.
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 a single sentence with no unnecessary words. It is front-loaded with the action and resource, making it immediately understandable.
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?
This is a simple tool with one optional parameter and an output schema, so the description need not explain return values. It covers the core functionality. However, it lacks any context about what 'the brain' refers to or how the summary is structured, which would be helpful but not essential given the tool's simplicity.
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 provides only 'days' with a default, and the description clarifies that it represents 'the last N days'. This adds meaning beyond the bare parameter name. Given the schema description coverage is 0% and there is a single parameter, the description compensates reasonably well by linking the parameter to the time window.
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 uses a specific verb ('Summarize') and a clear resource ('what was added to the brain in the last N days'). This distinguishes it from sibling tools like 'recall' (which likely retrieves specific information) and 'forget' (which removes).
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: when you need a summary of recent additions over a time window. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites.
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 discloses search algorithm (BM25), output format (relevant passages with timestamps and deep links), and relevance ordering. As a read-only search tool, this is adequate behavioral disclosure.
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 concise (3 sentences) and front-loaded with the core action. Every sentence adds value, though the first two sentences are somewhat redundant ('Search everything...' and 'Full-text search...') but not bloated.
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?
For a simple search tool with an output schema (not shown), the description explains return values and usage. It lacks details on `limit` semantics and scope (e.g., whether 'everything' is user-specific), but overall it is sufficiently complete for a low-complexity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage and the description does not directly explain `limit` or define `query` beyond an example. The example implies query is a natural language question, but `limit` is entirely omitted, leaving parameter semantics under-specified.
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 starts with a clear verb+resource: 'Search everything ever watched or listened to.' It further specifies full-text BM25 search across indexed transcripts, distinguishing from siblings like 'transcript' (retrieving one transcript) or 'library' (listing).
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 provides explicit usage context: 'Use this to answer questions like "what did that video say about X?"' and instructs to answer from returned passages with citations. It does not explicitly state when not to use, but the use case is clear.
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?
With no annotations provided, the description carries the burden of disclosing behavior. It communicates a read-only operation via 'Read' and adds the slicing behavior with start/end seconds. It does not mention error handling or response size, but the output schema exists and the behavior is simple.
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?
Two concise, front-loaded sentences deliver the core purpose and an optional feature without any wasted words. The structure is easy to scan and process.
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?
For a simple read tool with an output schema, the description adequately covers required input formats, optional parameters, and the slicing use case. It does not address edge cases like multiple title matches or not-found behavior, but these are not critical for a straightforward retrieval 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 description coverage is 0%, so the description compensates well. It explains that item_ref can be an id, URL, or title fragment, and that start/end are in seconds and optional for slicing. This adds meaningful semantics beyond the bare schema titles.
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 opens with a specific verb and resource ('Read the raw transcript of one item') and clarifies acceptable reference types (id, URL, or title fragment). This clearly distinguishes it from sibling tools like 'digest' or 'recall' by focusing on raw transcript retrieval.
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 provides clear context: use when you need the raw transcript of a single item, optionally limited to a time slice. It does not explicitly name alternatives or when-not-to-use conditions, but the purpose is specific enough to imply the right scenario.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adequately discloses the destructive nature ('Permanently delete') and the confirmation requirement ('nothing is deleted until the user approves'), which are key behavioral traits. It does not cover side effects or failure modes, but these are not critical for this simple tool.
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 two sentences long, front-loaded with the primary action, and each sentence adds essential information: the deletion action and the confirmation requirement. There is no redundancy or filler.
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?
For a simple one-parameter tool with an output schema, the description covers all essential aspects: what it does, what it accepts, and the critical confirmation flow. No missing information is needed for correct usage.
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 input schema only names the parameter 'item_ref' with no description, and schema coverage is 0%. The description compensates by explaining that the reference can be an id, URL, or title fragment, giving meaningful semantics beyond the schema. It could be more specific about the format of the id or fragment, but it provides sufficient guidance.
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 action ('Permanently delete an item') and specifies the target resource ('by id, URL, or title fragment'). It is distinct from sibling tools like 'remember' and 'recall', establishing a unique purpose for deletion.
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 provides clear context on when to use the tool (for deletion) and includes an important prerequisite (explicit user confirmation via MRTR elicitation flow). However, it does not explicitly mention alternatives or when not to use the tool, so it falls short of a 5.
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 behavioral burden. It discloses that the transcript is fetched, chunked with timestamps, and indexed for search, and that the tool returns the stored item's id. This is meaningful process transparency, though it omits potential edge cases like duplicate URLs or unsupported media types.
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 three sentences long, front-loads the core purpose, and each sentence adds distinct value: input types, processing behavior, and output usage. No filler or repetition of schema info.
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?
For a tool with two parameters and an output schema, the description covers input, processing pipeline, and return value, and connects to related tools. It lacks explicit constraints like authentication or format limitations, but given the output schema, this is sufficiently complete for an agent to use the tool correctly.
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%, so the description fully compensates. It explains that `url` accepts a YouTube URL or podcast RSS feed URL, and that `episode` is an optional title filter defaulting to the latest episode. Both parameters are semantically enriched beyond the bare 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 opens with a specific action and target: 'Add a YouTube video or podcast episode to the second brain.' It clearly distinguishes this from sibling tools (recall, library, transcript, digest, forget) by focusing on ingestion, not retrieval or deletion.
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?
It explains how to use the tool: pass a YouTube URL or podcast RSS feed, optionally with an episode filter defaulting to the latest episode. It also says the returned id should be used with `transcript` and `forget`, giving follow-up context. It does not explicitly state when not to use it, but the usage context is clear.
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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