Dev Context Memory MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clear, distinct purpose: append tools for adding structured entries, retrieval tools for accessing memory, and write for overwriting sections. No ambiguity between tools.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern in snake_case (e.g., append_api_contract, list_memory_sections), making the set predictable and easy to navigate.
Tool Count5/5
With 7 tools covering creation, retrieval, and overwriting of memory sections, the set is well-scoped. Each tool earns its place without being redundant or excessive.
Completeness3/5
The tools support appending and reading memory, but lack explicit delete or edit functionality for sections or individual entries. write_memory can overwrite but not delete, and no tool allows partial updates.
Average 4.3/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits 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
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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?
No annotations are provided, so the description must carry the behavioral burden. It describes what to store but does not disclose whether the tool overwrites or appends, or any side effects. The description is adequate but lacks details on behavior beyond storage.
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, front-loaded with the primary usage scenario. Every sentence adds value without redundancy. Very concise and well-structured.
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 10 parameters and no output schema, the description provides a clear overview of the tool's purpose and what the contract should contain. It covers the essential categories. Minor missing detail on formatting, but overall complete enough.
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%, so the schema already documents all parameters. The description lists the key fields (method, path, auth, etc.) but adds little extra meaning beyond that. Baseline score of 3 applies.
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 purpose: 'Use this tool after creating or modifying an API endpoint. Store only the durable endpoint contract.' It specifies the verb (store) and resource (API contract), and distinguishes itself by explicitly excluding full source code.
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 when-to-use guidance: 'after creating or modifying an API endpoint.' It also tells what not to store ('Do not store full source code.'). However, it does not directly contrast with sibling tools, though the context makes it clear that this is for API contracts specifically.
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 discloses key behaviors: keyword matching (not semantic), case-insensitive, returns lines with surrounding context, and searches all memory sections. However, it does not mention limitations like max results, pagination, or ordering. With no annotations, this provides moderate transparency but could be more thorough.
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 concise sentences. The first sentence front-loads the usage guidance, and the second explains the behavior. No superfluous words; each sentence adds essential value.
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?
Despite having only one parameter and no output schema, the description covers the tool's purpose, usage context, search mechanism, and return format. It could mention result limits or wildcard support, but it is largely complete for a simple 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?
Only one parameter (query) with 100% schema coverage. The description repeats the schema's description (case-insensitive keyword matching) without adding new meaning. According to guidance, when schema_coverage is high, baseline is 3, and the description offers no additional parameter-level insight.
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 explicitly states the tool's purpose: searching memory sections using keyword matching. It also specifies when to use it ('before scanning the codebase when the user asks about project architecture, API contracts, decisions, bugs, conventions, or previous implementation choices'), clearly distinguishing it from sibling tools like read_memory or list_memory_sections.
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 guidance on when to use this tool ('before scanning the codebase' for specific types of queries). It lacks explicit when-not-to-use instructions, but the context implies alternatives (e.g., scanning codebase for other queries). This still offers clear direction.
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 must cover behavioral aspects. It states the tool stores a structured record and warns against storing code. However, it does not disclose idempotency, overwrite behavior, or required permissions, which could be important for a write operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and usage. Every sentence adds value. No wasted words.
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 5 parameters, 3 required, no output schema, and no annotations, the description covers the core purpose, usage, and constraints. It lacks details about return value or error handling, but for a storage-oriented tool, the described aspects are sufficient.
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 coverage is 100%, so baseline is 3. The description adds value by explaining that parameters correspond to ADR fields and by explicitly warning against storing full source code, which clarifies the intended use of the parameters 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's purpose: record an architecture/design decision. It uses specific verbs ('Record', 'Stores') and names the output format (structured ADR). It distinguishes from sibling tools like append_api_contract by focusing on decisions.
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 explicit usage context: 'Use this after making a significant technical choice.' Also instructs what not to store ('Do not store full source code'). Could mention alternative tools for other purposes, but the context is clear.
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 the full burden. It implies a read-only operation with no side effects, but does not mention potential failure modes, rate limits, or whether the section must exist. The behavior is minimally disclosed.
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 that start with the action and purpose, immediately stating what the tool does and including a usage hint. Every sentence is necessary and no filler.
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 one parameter, the description covers purpose and usage. It lacks a description of the return value (output), but given no output schema, the agent can reasonably infer it returns the section's text. Adequate overall.
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 already has a 100% description coverage for the 'section' parameter with an explicit list. The description adds value by providing examples of the content types stored in each section, helping the agent understand what to retrieve.
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 reads a memory section to retrieve project context, and provides specific examples such as architecture decisions and conventions. It effectively distinguishes the read action from sibling tools that write, append, list, search, or summarize.
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 advises preferring reading memory before scanning unrelated source files, which gives a use-case preference. However, it does not explicitly contrast with sibling tools like search_memory or list_memory_sections, so it lacks clear exclusion criteria.
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 does not explicitly disclose behavioral traits such as being read-only or requiring any permissions. However, the tool's summary nature implies it is safe, and no contradictions exist.
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 purpose, and contains no filler or redundant information. Every sentence contributes meaning.
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 one optional parameter, no output schema, and a clear sibling set, the description adequately covers what the tool does, when to use it, and what it returns. No critical gaps remain.
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 for the single parameter is 100%, and its description in the schema already explains its optional nature and default behavior. The tool description does not add additional semantic value beyond what the schema provides, so a baseline score of 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 the tool's function: 'Get a compact overview of project memory. Returns headings and short excerpts for each section.' It specifies the verb (Get), resource (project memory), and output format, differentiating it from sibling tools like read_memory and search_memory.
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?
The description explicitly advises when to use the tool: 'Use this for a quick orientation before diving into specific sections with read_memory.' This provides clear context and mentions an alternative sibling tool, guiding correct selection.
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 provided, but the description transparently states this is a read-only listing operation returning section names and descriptions. No hidden behavior or contradictions.
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?
Three concise sentences front-load the purpose and usage. Every sentence 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?
Given zero parameters and no output schema, the description completely covers what the tool does and what it returns. No missing context.
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 schema coverage is 100%. The description adds value by mentioning the return structure (names and descriptions), which is sufficient for a parameterless tool.
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 memory sections with the purpose of discovering project context. It distinguishes from sibling tools like read_memory or search_memory by focusing on listing sections rather than content.
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?
Explicit guidance says to use this tool to discover what project context is stored. No alternatives are mentioned, but the use case is clear. Since there are no parameters, no when-not guidance is needed.
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 provided, so description carries full burden. It warns 'WARNING: This replaces the entire section. Use with care.' Discloses destructive behavior. Lacks details on reversibility or auth needs, but the warning is strong.
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 well-structured sentences. First states action and warning, second provides usage guidance with sibling references. No redundant words.
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 2 params and no output schema, description is thorough. It covers purpose, usage, and behavioral impact. Could optionally mention return format, but not necessary.
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 coverage is 100%, baseline 3. Description adds meaning: 'content' is 'new Markdown content' that 'will replace all existing content'. Adds context beyond 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 verb 'Overwrite' and resource 'memory section'. It distinguishes from sibling tools like append_decision and append_api_contract by specifying that write_memory is for replacing entire sections, not adding entries.
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 says 'Only use write_memory when you need to restructure or rewrite a full section' and 'Prefer append_decision or append_api_contract for adding entries'. Provides clear when-to and when-not-to context.
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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