Local Memory MCP
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a distinct, non-overlapping purpose: search retrieves, store adds, wipe deletes. No ambiguity between them.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern in snake_case (search_memory, store_memory, wipe_project_memories).
Tool Count5/53 tools cover the core operations for a local memory server (search, store, delete). The count is well-scoped and earns its place.
Completeness4/5The set covers essential memory operations, but lacks an update or list tool. However, delete+re-store can update, and search serves as discovery. Minor gap.
Average 4.4/5 across 3 of 3 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.
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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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears the full burden. It discloses the tool reads from vector memory and is embedding-based, but lacks details on side effects (e.g., no write operations implied), performance, or error states. The description is adequate but not exhaustive for a read-only search.
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 about 5 sentences and includes a structured list of example queries. It front-loads the core purpose and usage guidance. While clear and efficient, it could be slightly more concise without losing information; hence 4.
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?
Given 3 parameters (1 required) with full schema coverage, a known output schema, and sibling tools provided, the description achieves reasonable completeness. It covers usage timing and query formulation well. However, it briefly mentions the output schema exists but does not reference it, which is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does 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 value by providing example queries that illustrate how to use the `query` parameter effectively, going beyond the schema's simple description. This helps the agent formulate better queries, earning a 4.
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 it searches local vector memory for semantically similar context, with a specific verb ('search') and resource ('local vector memory'). It distinguishes from siblings (store_memory, wipe_project_memories) by focusing on retrieval. The embedding-based nature is explicitly mentioned, clarifying the tool's approach.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises calling this tool at the start of a task before reasoning or writing code, providing clear context. It explains that natural-language queries work better than exact terms. However, it does not explicitly mention when not to use it or direct alternatives, though sibling tools are listed separately.
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. It explains the tool stores text as semantic memory with persistence across sessions. Adds content quality guidance. Does not disclose output format, error handling, or storage limits, but for a store tool it provides reasonable transparency.
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?
Concise description with clear main sentence, followed by bulleted usage examples and a best practice note. No unnecessary words or repetition. Front-loaded with purpose.
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?
Given the tool's simplicity (3 parameters, required 1), description covers purpose, usage guidance, and parameter details adequately. Output is not described, but output schema likely covers that. Missing potential constraints like storage limits, but overall complete for the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds value: explains content should be focused; metadata is optional free-text or JSON, stored verbatim and not searched; project_tag is a logical namespace defaulting to global. These details enhance schema descriptions.
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?
Clearly states 'Store a piece of text as a semantic memory in the local vector database,' defining verb and resource. Distinguishes itself from siblings 'search_memory' and 'wipe_project_memories' as the creation tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to call: when user asks to remember something or when context should survive the session. Lists concrete examples (decisions, preferences, file paths, summaries). Provides best practice (one focused idea). Doesn't explicitly state when not to use, but guidance is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Clearly states irreversibility, immediate disk deletion, and what gets removed (vectors and metadata). No annotations provided, so description fully compensates by disclosing destructive nature.
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?
Three sentences: action+scope, consequences, usage guidance. No fluff. Front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Single-parameter tool with output schema. Description covers purpose, usage, behavior, and parameter semantics comprehensively. No gaps given simplicity and existing structured fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description already explains project_tag as namespace and global special case. Description adds context: 'namespace to wipe', examples, and clarifies scope. Adds value beyond schema despite 100% coverage.
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?
Description specifies exact verb ('Permanently delete') and resource ('all memories stored under project_tag'). Clearly distinguishes from siblings (search_memory, store_memory) by stating it's a destructive wipe operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to invoke ('only when the user has explicitly asked to clear or reset memory') and provides a caution ('when in doubt, confirm with user'). Also implies irreversibility, guiding appropriate use.
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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