Memory Bank MCP
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: get-memory-bank-info reads existing files, init-memory-bank creates the initial structure, and update-memory-bank provides instructions for modifications. The descriptions reinforce these distinct roles, making misselection unlikely.
Naming Consistency5/5All tool names follow a consistent verb-noun pattern with hyphens (get-memory-bank-info, init-memory-bank, update-memory-bank), using clear action verbs aligned with their functions. There are no deviations in naming style or convention.
Tool Count4/5Three tools are appropriate for the server's purpose of managing a memory bank, covering initialization, reading, and updating. However, the scope feels slightly thin as there is no tool for deleting or archiving files, which could be useful for lifecycle management.
Completeness4/5The tools cover core operations for a memory bank system: initialization, reading, and updating. A minor gap exists in lacking a delete or archive tool for full lifecycle coverage, but agents can likely work around this by using update-memory-bank to modify content as needed.
Average 3.9/5 across 3 of 3 tools scored. Lowest: 3.2/5.
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
- 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.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
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 carries the full burden of behavioral disclosure. It adds useful context: it generates 'detailed, actionable instructions' with 'direct operation commands (not requests for confirmation),' 'specific content templates,' and 'immediate execution emphasis.' This clarifies output format and urgency. However, it lacks details on permissions, side effects, or error handling, which are important for a tool that likely involves file updates.
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 well-structured and appropriately sized, with a clear opening sentence followed by bullet points that highlight key aspects. Each bullet adds value, such as detailing output components and execution emphasis. There's no redundant information, making it efficient, though it could be slightly more concise by integrating some points into the main sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a tool with 3 parameters (fully covered by schema), the description is moderately complete. It clarifies the tool's output format and urgency, which helps the agent understand what to expect. However, for a tool that likely involves file operations, it lacks details on potential side effects, success/failure indicators, or how the output should be used, leaving some gaps in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 three parameters thoroughly. The description adds no specific information about parameters beyond implying they relate to 'update instructions.' It doesn't explain how parameters like 'changeType' or 'rootPath' influence the generated instructions, so it provides minimal value beyond the schema. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate detailed Memory Bank file update instructions with immediate execution guidance.' It specifies the verb 'generate' and resource 'Memory Bank file update instructions,' making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'get-memory-bank-info' (likely for retrieval) or 'init-memory-bank' (likely for initialization), which slightly limits its distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. It mentions 'immediate execution emphasis for AI agents,' but this is a behavioral trait, not usage context. There's no indication of prerequisites, when to choose this over siblings, or any exclusions, leaving the agent without clear decision-making 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 full burden. It discloses that the tool reads files and returns formatted content, which is basic behavioral information. However, it lacks details on error handling (e.g., if the directory doesn't exist), performance implications (e.g., for large directories), or output structure beyond 'formatted content.'
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?
The description is front-loaded with the core purpose in the first sentence, followed by three bullet points that efficiently elaborate on scope, output, and usage without redundancy. Every sentence earns its place, and the structure is clear and concise.
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 low complexity (one parameter, no output schema, no annotations), the description is reasonably complete: it covers purpose, usage timing, and output intent. However, without annotations or an output schema, more detail on the return format (e.g., structure of 'formatted content') would enhance completeness for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the single parameter 'rootPath' with examples. The description adds no additional parameter information beyond what the schema provides, maintaining the baseline score of 3 for high schema 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?
The description clearly states the specific action ('Read and return all Memory Bank file contents'), identifies the resource ('.md files in the memory-bank directory'), and distinguishes from siblings by focusing on reading formatted content rather than initialization or updates. The comparison to 'codelf's get-project-info' further clarifies the purpose.
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?
Explicit guidance is provided: 'Use this tool at the beginning of each work session.' This directly tells the agent when to invoke it, and the mention of sibling tools (init-memory-bank, update-memory-bank) implies this is for reading existing content rather than creating or modifying it, though not explicitly stated.
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 clearly describes what the tool does (creates directory, generates files, reads projectBrief.md, provides guidance) and hints at overwriting behavior via the 'force' parameter. However, it does not cover potential side effects like file permissions, error handling, or specific output formats, leaving some behavioral aspects unspecified.
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?
The description is appropriately sized and front-loaded, starting with a clear purpose statement followed by a bulleted list of specific actions. Each sentence earns its place by adding value (e.g., detailing core file creation and projectBrief.md integration) without redundancy or unnecessary elaboration.
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 complexity (initialization with file operations), no annotations, and no output schema, the description is mostly complete. It covers key actions and parameters but lacks details on output (e.g., what 'next steps guidance' entails) and error scenarios. For a tool with 2 parameters and moderate complexity, it provides sufficient context but could be more thorough about behavioral outcomes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('force' and 'rootPath') with descriptions. The description does not add any additional meaning or context beyond what the schema provides, such as explaining how 'rootPath' interacts with the initialization process or default behaviors. Baseline 3 is appropriate as the schema handles parameter documentation adequately.
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 the tool's purpose with specific verbs ('Initialize', 'Create', 'Generate', 'Read and integrate', 'Provide') and resources ('memory-bank directory', 'core files', 'projectBrief.md', 'next steps guidance'). It distinguishes from siblings like 'get-memory-bank-info' (which likely reads) and 'update-memory-bank' (which likely modifies) by focusing on initial setup.
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 implies usage context (e.g., for initial setup of a memory bank) and mentions reading 'projectBrief.md if it exists', suggesting it's for new or existing projects. However, it lacks explicit guidance on when to use this tool versus alternatives like 'update-memory-bank' or 'get-memory-bank-info', and does not specify prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/hoppo-chan/memory-bank-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server