Strata Memory MCP Server

Server Quality Checklist

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Latest release: v0.2.0
Disambiguation5/5
Each tool targets a distinct purpose: initialization, health, profiling, memory writing, searching, recommendations, and session wake-up. No two tools have overlapping functionality that would confuse an agent.
Naming Consistency4/5
Most tools follow a verb_noun pattern (e.g., apply_memory_config, get_health, search_embedding_recommendations). However, 'strata_init' reverses the order (noun_verb) and 'memorize' is a lone verb without an object, causing slight inconsistency.
Tool Count5/5
With 8 tools, the surface is well-scoped and balanced for a memory management server. Each tool earns its place and covers core workflows without being excessively large or minimal.
Completeness3/5
The server covers initialization, health, profiling, memorizing, searching, and session wake-up, but lacks update and delete operations for memories. This gap may cause agents to fail when they need to modify or remove stored data.
Average 3.7/5 across 8 of 8 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 5 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
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?
No annotations are provided, so the description carries the full burden. It only states the return format ('flat Markdown') but does not disclose whether the tool modifies state, requires authentication, has side effects, or triggers any mutations. 'Wake-up' suggests activation but is vague.
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 very short (one sentence plus return note) and front-loaded with the action and key components. Every piece of information is essential, though jargon like 'L0 profile' could be clarified.
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?
For a tool with 4 parameters, no output schema, and complex multi-layered functionality (profile, diary, semantic search, CBT defusion), the description is too sparse. It fails to explain how the layers combine, what CBT defusion entails, or the format of the returned Markdown, leaving the agent under-informed.
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?
The input schema provides 100% parameter descriptions, so the baseline is 3. The tool description does not add new meaning beyond what the schema already conveys (e.g., the schema already defines 'context_depth' with enum choices). It mentions 'L2 semantic search' but does not elaborate on how parameters interact.
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 specifies the verb 'wake-up' and lists the resources involved (L0 profile, L1 diary, L2 semantic search) and the return format (flat Markdown). It distinguishes from sibling 'search' by including CBT defusion and multi-layer context.
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?
No guidance on when to use this tool versus siblings like 'search', 'memorize', or 'search_embedding_recommendations'. The description does not indicate prerequisites, use cases, or exclusions.
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?
The description reveals that the tool writes to both a Markdown drawer and a vector index, indicating persistence and indexing. However, it does not disclose potential side effects, overwrite behavior, or authorization requirements.
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 a single sentence that efficiently communicates the primary action and stored metadata. It is dense but not excessively long.
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?
With no output schema, the description does not explain return values or success indicators. Given the tool's complexity (6 parameters), it omits crucial details like error handling and post-conditions.
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?
Schema coverage is 100%, so baseline is 3. The description adds minimal value beyond the schema, mentioning metadata fields that are not parameters and not explaining existing parameters in more depth.
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 the tool records a conversation or fact into memory, specifying metadata fields. However, it mentions 'emotional_salience' and 'is_negative_schema' which are not present in the input schema, causing minor confusion.
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?
No guidance on when to use this tool versus alternatives like search or apply_memory_config. Lacks context for appropriate usage scenarios.
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 mentions filters and boosting but does not detail side effects, performance implications, or the meaning of 'state-dependent boosting'. It is moderately transparent but leaves gaps.
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 a single sentence, concise and front-loaded with key information. However, it could benefit from structured formatting to improve readability, given the number of concepts packed in.
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?
With 7 parameters, no output schema, and no annotations, the description adequately covers the purpose but omits details on return format, pagination behavior, and how boosting works. It is minimally complete for a complex search tool.
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?
Schema coverage is high (86%), so the baseline is 3. The description adds context about 'time/category/tag filters and state-dependent boosting' which aligns with schema parameters, but does not provide additional format or syntax details beyond what the schema already states.
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', the resource 'L2 memories', and specifies features like time/category/tag filters and state-dependent boosting. It is specific and distinguishes from sibling tools like search_embedding_recommendations by focusing on active semantic search across memories.
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 alternatives such as search_embedding_recommendations or memorize. It lacks explicit context about prerequisites, exclusions, or when not to use it.
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 must carry the behavioral burden. It specifies the tool returns a summary of runtime status with listed items, which provides moderate transparency. However, it does not mention any side effects, authentication needs, or reliability details.
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, front-loaded with 'Runtime status', and contains no unnecessary words. Every listed item is meaningful for understanding the output.
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 no parameters and no output schema, the description provides a reasonable overview. However, some terms like 'CBT' and 'vector/drawer count' are not explained, which may leave an agent unsure of their meaning.
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 has no parameters (coverage 100%), so the description adds value by enumerating the fields included in the output (initialized, mode, CBT, audit, vector/drawer count, config summary). This goes beyond the empty schema.
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 the tool returns 'Runtime status' and lists specific components like initialized, mode, CBT, audit, vector/drawer count, config summary. This makes the purpose evident. However, it does not differentiate from the sibling tool 'get_system_profile', which could be a similar status check.
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 the tool is used when runtime status is needed, but it gives no explicit when-to-use or when-not-to-use guidance. There is no mention of alternatives like 'get_system_profile'.
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 provided, so description carries full burden. Describes internal logic (MTEB-informed table) but does not disclose side effects, auth requirements, or what happens with invalid input.
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?
Single, front-loaded sentence with a tag. All content is relevant and concise with no wasted words.
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 no output schema, the description omits details about the return format (e.g., structure of ranked recommendations). Adequate for a simple lookup but could be more complete.
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?
Schema description coverage is 100% for the single parameter; the description repeats the same info. No additional meaning added beyond schema, meeting baseline for high coverage.
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?
Clearly states it returns ranked embedding recommendations based on hardware profile, using MTEB-informed lookup table. Distinct from sibling tools like get_system_profile (hardware probe) and search (general search).
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?
Implies usage when hardware-specific model recommendations are needed and notes auto-detection if profile omitted, but does not explicitly compare to alternatives or state when not to use.
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?
With no annotations, the description carries full burden. It discloses persistence and initialization of various components, but lacks details on destructiveness (e.g., overwriting existing config), error conditions, or required permissions.
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 sentences with no waste. Key information is front-loaded: agent-driven, apply config, list of actions, hot reload. Every sentence earns its place.
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 complexity (8 params, no output schema), the description covers the main effect adequately. It lacks details on return values and error handling, but the core purpose is clearly communicated.
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 baseline is 3. The description adds no extra meaning beyond the schema, merely referencing the overall action of persisting config.
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 ('Apply') and specific resource ('memory configuration'), listing concrete actions: persist config, initialize directories, ChromaDB, SQLite. It distinguishes itself from sibling tools like 'strata_init' or 'memorize' by focusing on configuration application.
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 implies usage when needing to apply a memory configuration and highlights hot reload support, but it does not explicitly state when to use versus alternatives or when not to use it.
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, the description carries full burden. It discloses that the tool performs initialization affecting system state, and details behaviors of each mode (CBT safety, 48h cooling, multi-tenancy, AuditLog). However, it does not specify whether the tool is idempotent or if it overrides existing configuration.
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 sentences, no redundancy. First sentence states purpose, second provides mode options and key features. Every word is informative and front-loaded.
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 7 parameters, no output schema, and no annotations, the description covers the main purpose and mode distinction. Missing details include return value, side effects of repeated calls, and explanation of '48h cooling.' Adequate but leaves gaps.
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?
The input schema has 100% description coverage for all 7 parameters, each well-documented with types, enums, and defaults. The description adds minimal value beyond the schema, only reinforcing the mode choice. Baseline 3 is appropriate.
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 this is for first-time initialization with a dual-mode setup. The verb 'initialization' and resource 'dual-mode setup' are specific, and it distinguishes itself from sibling tools like 'apply_memory_config' or 'memorize' by focusing on initial system configuration.
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 explicitly marks this as 'First-time initialization,' indicating it should be used at the start. It guides the choice between 'personal' and 'company' modes, but does not specify when not to use it (e.g., after initialization) or mention alternatives among siblings.
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?
Describes itself as 'silent' and returns information only. With no annotations, it does not explicitly confirm read-only or non-destructive behavior, but the description is sufficient for a simple query 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?
Extremely concise; one sentence covers purpose, output, and usage guidance. Every phrase adds value without redundancy.
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?
Despite no output schema, description fully informs what the tool returns and its recommended use during onboarding. No further context needed.
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?
No parameters exist, so the description adds no param info beyond the schema. Baseline 4 applies as schema coverage is 100%.
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?
Clearly states it performs hardware profiling and lists specific returned fields (OS, RAM, CPU cores, GPU accelerator). Distinguishes from siblings by noting it's for onboarding and requires no user input.
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?
Explicitly specifies when to use: call this first during onboarding. No ambiguity about its role as an initial profiling step.
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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